Mathematical model for water quality impact assessment and its computer application in coal mine water

International Nuclear Information System (INIS)

Sundararajan, M.; Chakraborty, M.K.; Gupta, J.P.; Saxena, N.C.; Dhar, B.B.

1994-01-01

This paper presents a mathematical model to assess the Water Quality Impact in coal mine or in river system by accurate and rational method. Algorithm, flowchart and computer programme have been developed upon this model to assess the quality of coal mine water. 3 refs., 2 figs., 2 tabs

A New Empirical Sewer Water Quality Model for the Prediction of WWTP Influent Quality

NARCIS (Netherlands)

Langeveld, J.G.; Schilperoort, R.P.S.; Rombouts, P.M.M.; Benedetti, L.; Amerlinck, Y.; de Jonge, J.; Flameling, T.; Nopens, I.; Weijers, S.

2014-01-01

Modelling of the integrated urban water system is a powerful tool to optimise wastewater system performance or to find cost-effective solutions for receiving water problems. One of the challenges of integrated modelling is the prediction of water quality at the inlet of a WWTP. Recent applications

Uncertainty analyses of the calibrated parameter values of a water quality model

Science.gov (United States)

Rode, M.; Suhr, U.; Lindenschmidt, K.-E.

2003-04-01

For river basin management water quality models are increasingly used for the analysis and evaluation of different management measures. However substantial uncertainties exist in parameter values depending on the available calibration data. In this paper an uncertainty analysis for a water quality model is presented, which considers the impact of available model calibration data and the variance of input variables. The investigation was conducted based on four extensive flowtime related longitudinal surveys in the River Elbe in the years 1996 to 1999 with varying discharges and seasonal conditions. For the model calculations the deterministic model QSIM of the BfG (Germany) was used. QSIM is a one dimensional water quality model and uses standard algorithms for hydrodynamics and phytoplankton dynamics in running waters, e.g. Michaelis Menten/Monod kinetics, which are used in a wide range of models. The multi-objective calibration of the model was carried out with the nonlinear parameter estimator PEST. The results show that for individual flow time related measuring surveys very good agreements between model calculation and measured values can be obtained. If these parameters are applied to deviating boundary conditions, substantial errors in model calculation can occur. These uncertainties can be decreased with an increased calibration database. More reliable model parameters can be identified, which supply reasonable results for broader boundary conditions. The extension of the application of the parameter set on a wider range of water quality conditions leads to a slight reduction of the model precision for the specific water quality situation. Moreover the investigations show that highly variable water quality variables like the algal biomass always allow a smaller forecast accuracy than variables with lower coefficients of variation like e.g. nitrate.

Calibration of Linked Hydrodynamic and Water Quality Model for Santa Margarita Lagoon

Science.gov (United States)

2016-07-01

was used to drive the transport and water quality kinetics for the simulation of 2007–2009. The sand berm, which controlled the opening/closure of...TECHNICAL REPORT 3015 July 2016 Calibration of Linked Hydrodynamic and Water Quality Model for Santa Margarita Lagoon Final Report Pei...Linked Hydrodynamic and Water Quality Model for Santa Margarita Lagoon Final Report Pei-Fang Wang Chuck Katz Ripan Barua SSC Pacific James

Evaluation of the Current State of Integrated Water Quality Modelling

Science.gov (United States)

Arhonditsis, G. B.; Wellen, C. C.; Ecological Modelling Laboratory

2010-12-01

Environmental policy and management implementation require robust methods for assessing the contribution of various point and non-point pollution sources to water quality problems as well as methods for estimating the expected and achieved compliance with the water quality goals. Water quality models have been widely used for creating the scientific basis for management decisions by providing a predictive link between restoration actions and ecosystem response. Modelling water quality and nutrient transport is challenging due a number of constraints associated with the input data and existing knowledge gaps related to the mathematical description of landscape and in-stream biogeochemical processes. While enormous effort has been invested to make watershed models process-based and spatially-distributed, there has not been a comprehensive meta-analysis of model credibility in watershed modelling literature. In this study, we evaluate the current state of integrated water quality modeling across the range of temporal and spatial scales typically utilized. We address several common modeling questions by providing a quantitative assessment of model performance and by assessing how model performance depends on model development. The data compiled represent a heterogeneous group of modeling studies, especially with respect to complexity, spatial and temporal scales and model development objectives. Beginning from 1992, the year when Beven and Binley published their seminal paper on uncertainty analysis in hydrological modelling, and ending in 2009, we selected over 150 papers fitting a number of criteria. These criteria involved publications that: (i) employed distributed or semi-distributed modelling approaches; (ii) provided predictions on flow and nutrient concentration state variables; and (iii) reported fit to measured data. Model performance was quantified with the Nash-Sutcliffe Efficiency, the relative error, and the coefficient of determination. Further, our

Water quality modelling in the San Antonio River Basin driven by radar rainfall data

OpenAIRE

Almoutaz Elhassan; Hongjie Xie; Ahmed A. Al-othman; James Mcclelland; Hatim O. Sharif

2016-01-01

Continuous monitoring of stream water quality is needed as it has significant impacts on human and ecological health and well-being. Estimating water quality between sampling dates requires model simulation based on the available geospatial and water quality data for a given watershed. Models such as the Soil and Water Assessment Tool (SWAT) can be used to estimate the missing water quality data. In this study, SWAT was used to estimate water quality at a monitoring station near the outlet of...

Coastal Water Quality Modeling in Tidal Lake: Revisited with Groundwater Intrusion

Science.gov (United States)

Kim, C.

2016-12-01

A new method for predicting the temporal and spatial variation of water quality, with accounting for a groundwater effect, has been proposed and applied to a water body partially connected to macro-tidal coastal waters in Korea. The method consists of direct measurement of environmental parameters, and it indirectly incorporates a nutrients budget analysis to estimate the submarine groundwater fluxes. Three-dimensional numerical modeling of water quality has been used with the directly collected data and the indirectly estimated groundwater fluxes. The applied area is Saemangeum tidal lake that is enclosed by 33km-long sea dyke with tidal openings at two water gates. Many investigations of groundwater impact reveal that 10 50% of nutrient loading in coastal waters comes from submarine groundwater, particularly in the macro-tidal flat, as in the west coast of Korea. Long-term monitoring of coastal water quality signals the possibility of groundwater influence on salinity reversal and on the excess mass outbalancing the normal budget in Saemangeum tidal lake. In the present study, we analyze the observed data to examine the influence of submarine groundwater, and then a box model is demonstrated for quantifying the influx and efflux. A three-dimensional numerical model has been applied to reproduce the process of groundwater dispersal and its effect on the water quality of Saemangeum tidal lake. The results show that groundwater influx during the summer monsoon then contributes significantly, 20% more than during dry season, to water quality in the tidal lake.

A Probabilistic Model for Propagating Ungauged Basin Runoff Prediction Variability and Uncertainty Into Estuarine Water Quality Dynamics and Water Quality-Based Management Decisions

Science.gov (United States)

Anderson, R.; Gronewold, A.; Alameddine, I.; Reckhow, K.

2008-12-01

The latest official assessment of United States (US) surface water quality indicates that pathogens are a leading cause of coastal shoreline water quality standard violations. Rainfall-runoff and hydrodynamic water quality models are commonly used to predict fecal indicator bacteria (FIB) concentrations in these waters and to subsequently identify climate change, land use, and pollutant mitigation scenarios which might improve water quality and lead to reinstatement of a designated use. While decay, settling, and other loss kinetics dominate FIB fate and transport in freshwater systems, previous authors identify tidal advection as a dominant fate and transport process in coastal estuaries. As a result, acknowledging hydrodynamic model input (e.g. watershed runoff) variability and parameter (e.g tidal dynamics parameter) uncertainty is critical to building a robust coastal water quality model. Despite the widespread application of watershed models (and associated model calibration procedures), we find model inputs and parameters are commonly encoded as deterministic point estimates (as opposed to random variables), an approach which effectively ignores potential sources of variability and uncertainty. Here, we present an innovative approach to building, calibrating, and propagating uncertainty and variability through a coupled data-based mechanistic (DBM) rainfall-runoff and tidal prism water quality model. While we apply the model to an ungauged tributary of the Newport River Estuary (one of many currently impaired shellfish harvesting waters in Eastern North Carolina), our model can be used to evaluate water quality restoration scenarios for coastal waters with a wide range of designated uses. We begin by calibrating the DBM rainfall-runoff model, as implemented in the IHACRES software package, using a regionalized calibration approach. We then encode parameter estimates as random variables (in the rainfall-runoff component of our comprehensive model) via the

Modeling Water Clarity and Light Quality in Oceans

Directory of Open Access Journals (Sweden)

Mohamed A. Abdelrhman

2016-11-01

Full Text Available Phytoplankton is a primary producer of organic compounds, and it forms the base of the food chain in ocean waters. The concentration of phytoplankton in the water column controls water clarity and the amount and quality of light that penetrates through it. The availability of adequate light intensity is a major factor in the health of algae and phytoplankton. There is a strong negative coupling between light intensity and phytoplankton concentration (e.g., through self-shading by the cells, which reduces available light and in return affects the growth rate of the cells. Proper modeling of this coupling is essential to understand primary productivity in the oceans. This paper provides the methodology to model light intensity in the water column, which can be included in relevant water quality models. The methodology implements relationships from bio-optical models, which use phytoplankton chlorophyll a (chl-a concentration as a surrogate for light attenuation, including absorption and scattering by other attenuators. The presented mathematical methodology estimates the reduction in light intensity due to absorption by pure seawater, chl-a pigment, non-algae particles (NAPs and colored dissolved organic matter (CDOM, as well as backscattering by pure seawater, phytoplankton particles and NAPs. The methods presented facilitate the prediction of the effects of various environmental and management scenarios (e.g., global warming, altered precipitation patterns, greenhouse gases on the wellbeing of phytoplankton communities in the oceans as temperature-driven chl-a changes take place.

Modeling of Water Quality 'Almendares River'

International Nuclear Information System (INIS)

Domínguez Catasús, Judith

2005-01-01

The river Almendares, one of the most important water bodies of the Havana City, is very polluted. The analysis of parameters as dissolved oxygen and biochemical oxygen demand is very helpful for the studies aimed to the recovery of the river. There is a growing recognition around the word that the water quality models are very useful tools to plan sanitary strategies for the handling of the contamination. In the present work, the advective, steady- state Streeter and Phelps model was validated to simulate the effect of the multiple-point and distributed sources on the carbonaceous oxygen demand, NH4 and dissolved oxygen. For modeling purposes the section of the river located between the point where the waste water treatment station Maria del Carmen discharges to the river and the Bridge El Bosque, was divided in 11 segments. The use of the 99mTc and the Rodamine WT as tracers allowed determining the hydrodynamic parameters necessary for modeling purposes. The validated model allows to predict the effect of the sanitary strategies on the water quality of the river. The main conclusions are: 1. The model Streeter and Phelps calibrated and validated in the Almendares between the confluence of the channel 'María del Carmen' and bridge the Forest of Havana, described in more than 90% The behavior of the dissolved oxygen and BODn (in terms of ammonia), and more than 85%, the carbonaceous demand oxygen, which characterizes the process of purification. 2. Model validation Streeter and Phelps, indicates that implicit conceptual model is appropriate. This refers primarily to the considerations relating to the calculation of the kinetic constants and the DOS, the segmentation used, to the location of the discharges and the Standing been about them, to the river morphology and hydrodynamic parameters . 3. The calibration procedure Streeter and Phelps model that determines the least-squares Kr-Kd pair that best fits the OD and uses this Kr to model BOD gets four% increase in

Projection pursuit water quality evaluation model based on chicken swam algorithm

Science.gov (United States)

Hu, Zhe

2018-03-01

In view of the uncertainty and ambiguity of each index in water quality evaluation, in order to solve the incompatibility of evaluation results of individual water quality indexes, a projection pursuit model based on chicken swam algorithm is proposed. The projection index function which can reflect the water quality condition is constructed, the chicken group algorithm (CSA) is introduced, the projection index function is optimized, the best projection direction of the projection index function is sought, and the best projection value is obtained to realize the water quality evaluation. The comparison between this method and other methods shows that it is reasonable and feasible to provide decision-making basis for water pollution control in the basin.

Water quality modelling and optimisation of wastewater treatment network using mixed integer programming

CSIR Research Space (South Africa)

Mahlathi, Christopher

2016-10-01

Full Text Available Instream water quality management encompasses field monitoring and utilisation of mathematical models. These models can be coupled with optimisation techniques to determine more efficient water quality management alternatives. Among these activities...

Water quality modeling of the Medellin river in the Aburrá Valley

OpenAIRE

Giraldo-B., Lina Claudia; Palacio, Carlos Alberto; Molina, Rubén; Agudelo, Rubén Alberto

2015-01-01

Water quality modeling intends to represent a water body in order to assess their status and project the effects of different measures taken for their protection. This paper presents the results obtained from the Qual2kw model implementation in the first 50 kilometers of the Aburrá-Medellín River, in their most critical conditions of water quality, which correspond to low flow rates. After the model calibration, three recovery scenarios (short-term, medium-term and long-term) were evaluated. ...

Root zone water quality model (RZWQM2): Model use, calibration and validation

Science.gov (United States)

Ma, Liwang; Ahuja, Lajpat; Nolan, B.T.; Malone, Robert; Trout, Thomas; Qi, Z.

2012-01-01

The Root Zone Water Quality Model (RZWQM2) has been used widely for simulating agricultural management effects on crop production and soil and water quality. Although it is a one-dimensional model, it has many desirable features for the modeling community. This article outlines the principles of calibrating the model component by component with one or more datasets and validating the model with independent datasets. Users should consult the RZWQM2 user manual distributed along with the model and a more detailed protocol on how to calibrate RZWQM2 provided in a book chapter. Two case studies (or examples) are included in this article. One is from an irrigated maize study in Colorado to illustrate the use of field and laboratory measured soil hydraulic properties on simulated soil water and crop production. It also demonstrates the interaction between soil and plant parameters in simulated plant responses to water stresses. The other is from a maize-soybean rotation study in Iowa to show a manual calibration of the model for crop yield, soil water, and N leaching in tile-drained soils. Although the commonly used trial-and-error calibration method works well for experienced users, as shown in the second example, an automated calibration procedure is more objective, as shown in the first example. Furthermore, the incorporation of the Parameter Estimation Software (PEST) into RZWQM2 made the calibration of the model more efficient than a grid (ordered) search of model parameters. In addition, PEST provides sensitivity and uncertainty analyses that should help users in selecting the right parameters to calibrate.

Accounting for and predicting the influence of spatial autocorrelation in water quality modeling

Science.gov (United States)

Miralha, L.; Kim, D.

2017-12-01

Although many studies have attempted to investigate the spatial trends of water quality, more attention is yet to be paid to the consequences of considering and ignoring the spatial autocorrelation (SAC) that exists in water quality parameters. Several studies have mentioned the importance of accounting for SAC in water quality modeling, as well as the differences in outcomes between models that account for and ignore SAC. However, the capacity to predict the magnitude of such differences is still ambiguous. In this study, we hypothesized that SAC inherently possessed by a response variable (i.e., water quality parameter) influences the outcomes of spatial modeling. We evaluated whether the level of inherent SAC is associated with changes in R-Squared, Akaike Information Criterion (AIC), and residual SAC (rSAC), after accounting for SAC during modeling procedure. The main objective was to analyze if water quality parameters with higher Moran's I values (inherent SAC measure) undergo a greater increase in R² and a greater reduction in both AIC and rSAC. We compared a non-spatial model (OLS) to two spatial regression approaches (spatial lag and error models). Predictor variables were the principal components of topographic (elevation and slope), land cover, and hydrological soil group variables. We acquired these data from federal online sources (e.g. USGS). Ten watersheds were selected, each in a different state of the USA. Results revealed that water quality parameters with higher inherent SAC showed substantial increase in R² and decrease in rSAC after performing spatial regressions. However, AIC values did not show significant changes. Overall, the higher the level of inherent SAC in water quality variables, the greater improvement of model performance. This indicates a linear and direct relationship between the spatial model outcomes (R² and rSAC) and the degree of SAC in each water quality variable. Therefore, our study suggests that the inherent level of

BOD-DO modeling and water quality analysis of a waste water outfall off Kochi, west coast of India

Digital Repository Service at National Institute of Oceanography (India)

Babu, M.T.; Das, V.K.; Vethamony, P.

Water quality scenarios around an offshore outfall off Kochi were simulated using MIKE21 water quality model, assuming a high Biochemical Oxygen Demand (BOD=50 mgl sup(-1)) effluent discharge. The discharge is introduced into the model through...

Terminology and methodology in modelling for water quality management

DEFF Research Database (Denmark)

Carstensen, J.; Vanrolleghem, P.; Rauch, W.

1997-01-01

There is a widespread need for a common terminology in modelling for water quality management. This paper points out sources of confusion in the communication between researchers due to misuse of existing terminology or use of unclear terminology. The paper attempts to clarify the context...... of the most widely used terms for characterising models and within the process of model building. It is essential to the ever growing society of researchers within water quality management, that communication is eased by establishing a common terminology. This should not be done by giving broader definitions...... of the terms, but by stressing the use of a stringent terminology. Therefore, the goal of the paper is to advocate the use of such a well defined and clear terminology. (C) 1997 IAWQ. Published by Elsevier Science Ltd....

[Review on HSPF model for simulation of hydrology and water quality processes].

Science.gov (United States)

Li, Zhao-fu; Liu, Hong-Yu; Li, Yan

2012-07-01

Hydrological Simulation Program-FORTRAN (HSPF), written in FORTRAN, is one ol the best semi-distributed hydrology and water quality models, which was first developed based on the Stanford Watershed Model. Many studies on HSPF model application were conducted. It can represent the contributions of sediment, nutrients, pesticides, conservatives and fecal coliforms from agricultural areas, continuously simulate water quantity and quality processes, as well as the effects of climate change and land use change on water quantity and quality. HSPF consists of three basic application components: PERLND (Pervious Land Segment) IMPLND (Impervious Land Segment), and RCHRES (free-flowing reach or mixed reservoirs). In general, HSPF has extensive application in the modeling of hydrology or water quality processes and the analysis of climate change and land use change. However, it has limited use in China. The main problems with HSPF include: (1) some algorithms and procedures still need to revise, (2) due to the high standard for input data, the accuracy of the model is limited by spatial and attribute data, (3) the model is only applicable for the simulation of well-mixed rivers, reservoirs and one-dimensional water bodies, it must be integrated with other models to solve more complex problems. At present, studies on HSPF model development are still undergoing, such as revision of model platform, extension of model function, method development for model calibration, and analysis of parameter sensitivity. With the accumulation of basic data and imorovement of data sharing, the HSPF model will be applied more extensively in China.

One multi-media environmental system with linkage between meteorology/ hydrology/ air quality models and water quality model

Science.gov (United States)

Tang, C.; Lynch, J. A.; Dennis, R. L.

2016-12-01

The biogeochemical processing of nitrogen and associated pollutants is driven by meteorological and hydrological processes in conjunction with pollutant loading. There are feedbacks between meteorology and hydrology that will be affected by land-use change and climate change. Changes in meteorology will affect pollutant deposition. It is important to account for those feedbacks and produce internally consistent simulations of meteorology, hydrology, and pollutant loading to drive the (watershed/water quality) biogeochemical models. In this study, the ecological response to emission reductions in streams in the Potomac watershed was evaluated. Firstly, we simulated the deposition by using the fully coupled Weather Research & Forecasting (WRF) model and the Community Multiscale Air Quality (CAMQ) model; secondly, we created the hydrological data by the offline linked Variable Infiltration Capacity (VIC) model and the WRF model. Lastly, we investigated the water quality by one comprehensive/environment model, namely the linkage of CMAQ, WRF, VIC and the Model of Acidification of Groundwater In Catchment (MAGIC) model from 2002 to 2010.The simulated results (such as NO3, SO4, and SBC) fit well to the observed values. The linkage provides a generally accurate, well-tested tool for evaluating sensitivities to varying meteorology and environmental changes on acidification and other biogeochemical processes, with capability to comprehensively explore strategic policy and management design.

Advanced Water Quality Modelling in Marine Systems: Application to the Wadden Sea, the Netherlands

Science.gov (United States)

Boon, J.; Smits, J. G.

2006-12-01

There is an increasing demand for knowledge and models that arise from water management in relation to water quality, sediment quality (ecology) and sediment accumulation (ecomorphology). Recently, models for sediment diagenesis and erosion developed or incorporated by Delft Hydraulics integrates the relevant physical, (bio)chemical and biological processes for the sediment-water exchange of substances. The aim of the diagenesis models is the prediction of both sediment quality and the return fluxes of substances such as nutrients and micropollutants to the overlying water. The resulting so-called DELWAQ-G model is a new, generic version of the water and sediment quality model of the DELFT3D framework. One set of generic water quality process formulations is used to calculate process rates in both water and sediment compartments. DELWAQ-G involves the explicit simulation of sediment layers in the water quality model with state-of-the-art process kinetics. The local conditions in a water layer or sediment layer such as the dissolved oxygen concentration determine if and how individual processes come to expression. New processes were added for sulphate, sulphide, methane and the distribution of the electron-acceptor demand over dissolved oxygen, nitrate, sulphate and carbon dioxide. DELWAQ-G also includes the dispersive and advective transport processes in the sediment and across the sediment-water interface. DELWAQ-G has been applied for the Wadden Sea. A very dynamic tidal and ecologically active estuary with a complex hydrodynamic behaviour located at the north of the Netherlands. The predicted profiles in the sediment reflect the typical interactions of diagenesis processes.

Surface Water Quality Evaluation Based on a Game Theory-Based Cloud Model

Directory of Open Access Journals (Sweden)

Bing Yang

2018-04-01

Full Text Available Water quality evaluation is an essential measure to analyze water quality. However, excessive randomness and fuzziness affect the process of evaluation, thus reducing the accuracy of evaluation. Therefore, this study proposed a cloud model for evaluating the water quality to alleviate this problem. Analytic hierarchy process and entropy theory were used to calculate the subjective weight and objective weight, respectively, and then they were coupled as a combination weight (CW via game theory. The proposed game theory-based cloud model (GCM was then applied to the Qixinggang section of the Beijiang River. The results show that the CW ranks fecal coliform as the most important factor, followed by total nitrogen and total phosphorus, while biochemical oxygen demand and fluoride were considered least important. There were 19 months (31.67% at grade I, 39 months (65.00% at grade II, and one month at grade IV and grade V during 2010–2014. A total of 52 months (86.6% of GCM were identical to the comprehensive evaluation result (CER. The obtained water quality grades of GCM are close to the grades of the analytic hierarchy process weight (AHPW due to the weight coefficient of AHPW set to 0.7487. Generally, one or two grade gaps exist among the results of the three groups of weights, suggesting that the index weight is not particularly sensitive to the cloud model. The evaluated accuracy of water quality can be improved by modifying the quantitative boundaries. This study could provide a reference for water quality evaluation, prevention, and improvement of water quality assessment and other applications.

Water quality diagnosis system

International Nuclear Information System (INIS)

Nagase, Makoto; Asakura, Yamato; Sakagami, Masaharu

1989-01-01

By using a model representing a relationship between the water quality parameter and the dose rate in primary coolant circuits of a water cooled reactor, forecasting for the feature dose rate and abnormality diagnosis for the water quality are conducted. The analysis model for forecasting the reactor water activity or the dose rate receives, as the input, estimated curves for the forecast Fe, Ni, Co concentration in feedwater or reactor water pH, etc. from the water quality data in the post and forecasts the future radioactivity or dose rate in the reactor water. By comparing the result of the forecast and the setting value such as an aimed value, it can be seen whether the water quality at present or estimated to be changed is satisfactory or not. If the quality is not satisfactory, it is possible to take an early countermeasure. Accordingly, the reactor water activity and the dose rate can be kept low. Further, the basic system constitution, diagnosis algorithm, indication, etc. are identical between BWR and PWR reactors, except for only the difference in the mass balance. (K.M.)

Studies on kinetics of water quality factors to establish water transparency model in Neijiang River, China.

Science.gov (United States)

Li, Ronghui; Pan, Wei; Guo, Jinchuan; Pang, Yong; Wu, Jianqiang; Li, Yiping; Pan, Baozhu; Ji, Yong; Ding, Ling

2014-05-01

The basis for submerged plant restoration in surface water is to research the complicated dynamic mechanism of water transparency. In this paper, through the impact factor analysis of water transparency, the suspended sediment, dissolved organic matter, algae were determined as three main impactfactors for water transparency of Neijiang River in Eastern China. And the multiple regression equation of water transparency and sediment concentration, permanganate index, chlorophyll-a concentration was developed. Considering the complicated transport and transformation of suspended sediment, dissolved organic matter and algae, numerical model of them were developed respectively for simulating the dynamic process. Water transparency numerical model was finally developed by coupling the sediment, water quality, and algae model. These results showed that suspended sediment was a key factor influencing water transparency of Neijiang River, the influence of water quality indicated by chemical oxygen demand and algal concentration indicated by chlorophyll a were indeterminate when their concentrations were lower, the influence was more obvious when high concentrations are available, such three factors showed direct influence on water transparency.

A One-Dimensional Hydrodynamic and Water Quality Model for a Water Transfer Project with Multihydraulic Structures

OpenAIRE

Yujun Yi; Caihong Tang; Zhifeng Yang; Shanghong Zhang; Cheng Zhang

2017-01-01

The long Middle Route of the South to North Water Transfer Project is composed of complex hydraulic structures (aqueduct, tunnel, control gate, diversion, culvert, and diverted siphon), which generate complex flow patterns. It is vital to simulate the flow patterns through hydraulic structures, but it is a challenging work to protect water quality and maintain continuous water transfer. A one-dimensional hydrodynamic and water quality model was built to understand the flow and pollutant movem...

Modeling water quality in an urban river using hydrological factors--data driven approaches.

Science.gov (United States)

Chang, Fi-John; Tsai, Yu-Hsuan; Chen, Pin-An; Coynel, Alexandra; Vachaud, Georges

2015-03-15

Contrasting seasonal variations occur in river flow and water quality as a result of short duration, severe intensity storms and typhoons in Taiwan. Sudden changes in river flow caused by impending extreme events may impose serious degradation on river water quality and fateful impacts on ecosystems. Water quality is measured in a monthly/quarterly scale, and therefore an estimation of water quality in a daily scale would be of good help for timely river pollution management. This study proposes a systematic analysis scheme (SAS) to assess the spatio-temporal interrelation of water quality in an urban river and construct water quality estimation models using two static and one dynamic artificial neural networks (ANNs) coupled with the Gamma test (GT) based on water quality, hydrological and economic data. The Dahan River basin in Taiwan is the study area. Ammonia nitrogen (NH3-N) is considered as the representative parameter, a correlative indicator in judging the contamination level over the study. Key factors the most closely related to the representative parameter (NH3-N) are extracted by the Gamma test for modeling NH3-N concentration, and as a result, four hydrological factors (discharge, days w/o discharge, water temperature and rainfall) are identified as model inputs. The modeling results demonstrate that the nonlinear autoregressive with exogenous input (NARX) network furnished with recurrent connections can accurately estimate NH3-N concentration with a very high coefficient of efficiency value (0.926) and a low RMSE value (0.386 mg/l). Besides, the NARX network can suitably catch peak values that mainly occur in dry periods (September-April in the study area), which is particularly important to water pollution treatment. The proposed SAS suggests a promising approach to reliably modeling the spatio-temporal NH3-N concentration based solely on hydrological data, without using water quality sampling data. It is worth noticing that such estimation can be

Water Quality Analysis Simulation

Data.gov (United States)

U.S. Environmental Protection Agency — The Water Quality analysis simulation Program, an enhancement of the original WASP. This model helps users interpret and predict water quality responses to natural...

Puget Sound Dissolved Oxygen Modeling Study: Development of an Intermediate Scale Water Quality Model

Energy Technology Data Exchange (ETDEWEB)

Khangaonkar, Tarang; Sackmann, Brandon S.; Long, Wen; Mohamedali, Teizeen; Roberts, Mindy

2012-10-01

The Salish Sea, including Puget Sound, is a large estuarine system bounded by over seven thousand miles of complex shorelines, consists of several subbasins and many large inlets with distinct properties of their own. Pacific Ocean water enters Puget Sound through the Strait of Juan de Fuca at depth over the Admiralty Inlet sill. Ocean water mixed with freshwater discharges from runoff, rivers, and wastewater outfalls exits Puget Sound through the brackish surface outflow layer. Nutrient pollution is considered one of the largest threats to Puget Sound. There is considerable interest in understanding the effect of nutrient loads on the water quality and ecological health of Puget Sound in particular and the Salish Sea as a whole. The Washington State Department of Ecology (Ecology) contracted with Pacific Northwest National Laboratory (PNNL) to develop a coupled hydrodynamic and water quality model. The water quality model simulates algae growth, dissolved oxygen, (DO) and nutrient dynamics in Puget Sound to inform potential Puget Sound-wide nutrient management strategies. Specifically, the project is expected to help determine 1) if current and potential future nitrogen loadings from point and non-point sources are significantly impairing water quality at a large scale and 2) what level of nutrient reductions are necessary to reduce or control human impacts to DO levels in the sensitive areas. The project did not include any additional data collection but instead relied on currently available information. This report describes model development effort conducted during the period 2009 to 2012 under a U.S. Environmental Protection Agency (EPA) cooperative agreement with PNNL, Ecology, and the University of Washington awarded under the National Estuary Program

Water quality modelling in the San Antonio River Basin driven by radar rainfall data

Directory of Open Access Journals (Sweden)

Almoutaz Elhassan

2016-05-01

Full Text Available Continuous monitoring of stream water quality is needed as it has significant impacts on human and ecological health and well-being. Estimating water quality between sampling dates requires model simulation based on the available geospatial and water quality data for a given watershed. Models such as the Soil and Water Assessment Tool (SWAT can be used to estimate the missing water quality data. In this study, SWAT was used to estimate water quality at a monitoring station near the outlet of the San Antonio River. Precipitation data from both rain gauges and weather radar were used to force the SWAT simulations. Virtual rain gauges which were based on weather radar data were created in the approximate centres of the 163 sub-watersheds of the San Antonio River Basin for SWAT simulations. This method was first tested in a smaller watershed in the middle of the Guadalupe River Basin resulting in increased model efficiency in simulating surface run-off. The method was then applied to the San Antonio River watershed and yielded good simulations for surface run-off (R2 = 0.7, nitrate (R2 = 0.6 and phosphate (R2 = 0.5 at the watershed outlet (Goliad, TX – USGS (United States Geological Survey gauge as compared to observed data. The study showed that the proper use of weather radar precipitation in SWAT model simulations improves the estimation of missing water quality data.

Comparison of computer models for estimating hydrology and water quality in an agricultural watershed

Science.gov (United States)

Various computer models, ranging from simple to complex, have been developed to simulate hydrology and water quality from field to watershed scales. However, many users are uncertain about which model to choose when estimating water quantity and quality conditions in a watershed. This study compared...

River water quality modelling under drought situations – the Turia River case

Directory of Open Access Journals (Sweden)

J. Paredes-Arquiola

2016-10-01

Full Text Available Drought and water shortage effects are normally exacerbated due to collateral impacts on water quality, since low streamflow affects water quality in rivers and water uses depend on it. One of the most common problems during drought conditions is maintaining a good water quality while securing the water supply to demands. This research analyses the case of the Turia River Water Resource System located in Eastern Spain. Its main water demand comes as urban demand from Valencia City, which intake is located in the final stretch of the river, where streamflow may become very low during droughts. As a result, during drought conditions concentrations of pathogens and other contaminants increase, compromising the water supply to Valencia City. In order to define possible solutions for the above-mentioned problem, we have developed an integrated model for simulating water management and water quality in the Turia River Basin to propose solutions for water quality problems under water scarcity. For this purpose, the Decision Support System Shell AQUATOOL has been used. The results demonstrate the importance of applying environmental flows as a measure of reducing pollutant's concentration depending on the evolution of a drought event and the state of the water resources system.

WATGIS: A GIS-Based Lumped Parameter Water Quality Model

Science.gov (United States)

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2002-01-01

A Geographic Information System (GIS)­based, lumped parameter water quality model was developed to estimate the spatial and temporal nitrogen­loading patterns for lower coastal plain watersheds in eastern North Carolina. The model uses a spatially distributed delivery ratio (DR) parameter to account for nitrogen retention or loss along a drainage network. Delivery...

Water Quality Analysis Simulation

Science.gov (United States)

The Water Quality analysis simulation Program, an enhancement of the original WASP. This model helps users interpret and predict water quality responses to natural phenomena and man-made pollution for variious pollution management decisions.

Work Plan for a Water Quality Model of Florida Bay

National Research Council Canada - National Science Library

Dortch, Mark

1997-01-01

.... The model is required to address issues pertaining to nutrient inputs and associated impacts on water quality and sea grass, particularly as related to changes in freshwater inflows from south...

Integrated Modelling on Flow and Water Quality Under the Impacts of Climate Change and Agricultural Activities

Science.gov (United States)

SHI, J.

2014-12-01

Climate change is expected to have a significant impact on flooding in the UK, inducing more intense and prolonged storms. Frequent flooding due to climate change already exacerbates catchment water quality. Land use is another contributing factor to poor water quality. For example, the move to intensive farming could cause an increase in faecal coliforms entering the water courses. In an effort to understand better the effects on water quality from land use and climate change, the hydrological and estuarine processes are being modelled using SWAT (Soil and Water Assessment Tool), linked to a 2-D hydrodynamic model DIVAST(Depth Integrated Velocity and Solute Transport). The coupled model is able to quantify how much of each pollutant from the catchment reaches the harbour and the impact on water quality within the harbour. The work is focused on the transportation and decay of faecal coliforms from agricultural runoff into the rivers Frome and Piddle in the UK. The impact from the agricultural land use and activities on the catchment river hydrology and water quality are evaluated. The coupled model calibration and validation showed the good model performance on flow and faecal coliform in the watershed and estuary.

Hyperspectral water quality retrieval model: taking Malaysia inshore sea area as an example

Science.gov (United States)

Cui, Tingwei; Zhang, Jie; Ma, Yi; Li, Jing; Lim, Boonleong; Roslinah, Samad

2007-11-01

Remote sensing technique provides the possibility of rapid and synchronous monitoring in a large area of the water quality, which is an important element for the aquatic ecosystem quality assessment of islands and coastal zones, especially for the nearshore and tourism sea area. Tioman Island of Malaysia is regarded as one of ten of the best islands in the world and attracts tourists from all over the world for its clear sea, beautiful seashore and charming scenery. In this paper, on the basis of in situ dataset in the study area, distribution discipline of water quality parameters is analyzed to find that phytoplankton pigment, rather than suspended sediment is the main water quality parameter in the study area; seawater there is clean but not very oligotrophic; seawater spectra contains distinct features. Then water quality hyperspectral retrieval models are developed based on in situ data to calculate the chlorophyll a concentration ([chl-a]), transparency (SD) with satisfactory performance. It's suggested that model precision should be validated further using more in-situ data.

Developing hydrological model for water quality in Iraq marshes zone using Landsat-TM

Science.gov (United States)

Marghany, Maged; Hasab, Hashim Ali; Mansor, Shattri; Shariff, Abdul Rashid Bin Mohamed

2016-06-01

The Mesopotamia marshlands constitute the largest wetland ecosystem in the Middle East and Western Eurasia. These wetlands are located at the confluence of the Tigris and Euphrates Rivers in southern Iraq. However, there are series reductions in the wetland zones because of neighbor countries, i.e. Turkey, Syria built dams upstream of Tigris and Euphrates Rivers. In addition, the first Gulf war of the 1980s had damaged majority of the marches resources. In fact,the marshes had been reduced in size to less than 7% since 1973 and had deteriorated in water quality parameters. The study integrates Hydrological Model of RMA-2 with Geographic Information System, and remote sensing techniques to map the water quality in the marshlands south of Iraq. This study shows that RMA-2 shows the two dimensional water flow pattern and water quality quantities in the marshlands. It can be said that the integration between Hydrological Model of RMA-2, Geographic Information System, and remote sensing techniques can be used to monitor water quality in the marshlands south of Iraq.

Numerical and Qualitative Contrasts of Two Statistical Models for Water Quality Change in Tidal Waters

Science.gov (United States)

Two statistical approaches, weighted regression on time, discharge, and season and generalized additive models, have recently been used to evaluate water quality trends in estuaries. Both models have been used in similar contexts despite differences in statistical foundations and...

A sediment resuspension and water quality model of Lake Okeechobee

Science.gov (United States)

James, R.T.; Martin, J.; Wool, T.; Wang, P.-F.

1997-01-01

The influence of sediment resuspension on the water quality of shallow lakes is well documented. However, a search of the literature reveals no deterministic mass-balance eutrophication models that explicitly include resuspension. We modified the Lake Okeeehobee water quality model - which uses the Water Analysis Simulation Package (WASP) to simulate algal dynamics and phosphorus, nitrogen, and oxygen cycles - to include inorganic suspended solids and algorithms that: (1) define changes in depth with changes in volume; (2) compute sediment resuspension based on bottom shear stress; (3) compute partition coefficients for ammonia and ortho-phosphorus to solids; and (4) relate light attenuation to solids concentrations. The model calibration and validation were successful with the exception of dissolved inorganic nitrogen species which did not correspond well to observed data in the validation phase. This could be attributed to an inaccurate formulation of algal nitrogen preference and/or the absence of nitrogen fixation in the model. The model correctly predicted that the lake is lightlimited from resuspended solids, and algae are primarily nitrogen limited. The model simulation suggested that biological fluxes greatly exceed external loads of dissolved nutrients; and sedimentwater interactions of organic nitrogen and phosphorus far exceed external loads. A sensitivity analysis demonstrated that parameters affecting resuspension, settling, sediment nutrient and solids concentrations, mineralization, algal productivity, and algal stoichiometry are factors requiring further study to improve our understanding of the Lake Okeechobee ecosystem.

Water quality modeling in the dead end sections of drinking water distribution networks.

Science.gov (United States)

Abokifa, Ahmed A; Yang, Y Jeffrey; Lo, Cynthia S; Biswas, Pratim

2016-02-01

Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of the distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used to calibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variations in flow demands on the simulation accuracy. A set of three correction factors were analytically derived to adjust residence time, dispersion rate and wall demand to overcome simulation error caused by spatial aggregation approximation. The current model results show better agreement with field-measured concentrations of conservative fluoride tracer and free chlorine disinfectant than the simulations of recent advection dispersion reaction models published in the literature. Accuracy of the simulated

Instruments for integrated water resources management : water quality modeling for sustainable wastewater management

NARCIS (Netherlands)

Barjoveanu, George; Teodosiu, Carmen; Cojocariu, Claudia; Augustijn, Dionysius C.M.; Craciun, Ioan

2013-01-01

This study presents the development and use of a hydraulic-coupled water quality model for the simulation of Biochemical Oxygen Demand (BOD) concentrations in the Bahlui River, a small river located in northeastern Romania. This river experiences the typical pollution problems for many Romanian

Water quantity and quality optimization modeling of dams operation based on SWAT in Wenyu River Catchment, China.

Science.gov (United States)

Zhang, Yongyong; Xia, Jun; Chen, Junfeng; Zhang, Minghua

2011-02-01

Water quantity and quality joint operation is a new mode in the present dams' operation research. It has become a hot topic in governmental efforts toward integrated basin improvement. This paper coupled a water quantity and quality joint operation model (QCmode) and genetic algorithm with Soil and Water Assessment Tool (SWAT). Together, these tools were used to explore a reasonable operation of dams and floodgates at the basin scale. Wenyu River Catchment, a key area in Beijing, was selected as the case study. Results showed that the coupled water quantity and quality model of Wenyu River Catchment more realistically simulates the process of water quantity and quality control by dams and floodgates. This integrated model provides the foundation for research of water quantity and quality optimization on dam operation in Wenyu River Catchment. The results of this modeling also suggest that current water quality of Wenyu River will improve following the implementation of the optimized operation of the main dams and floodgates. By pollution control and water quantity and quality joint operation of dams and floodgates, water quality of Wenyu river will change significantly, and the available water resources will increase by 134%, 32%, 17%, and 82% at the downstream sites of Sha River Reservoir, Lutong Floodgate, Xinpu Floodgate, and Weigou Floodgate, respectively. The water quantity and quality joint operation of dams will play an active role in improving water quality and water use efficiency in Wenyu River Basin. The research will provide the technical support for water pollution control and ecological restoration in Wenyu River Catchment and could be applied to other basins with large number of dams. Its application to the Wenyu River Catchment has a great significance for the sustainable economic development of Beijing City.

Integrity Model Application: A Quality Support System for Decision-makers on Water Quality Assessment and Improvement

Science.gov (United States)

Mirauda, D.; Ostoich, M.; Di Maria, F.; Benacchio, S.; Saccardo, I.

2018-03-01

In this paper, a mathematical model has been applied to a river in North-East Italy to describe vulnerability scenarios due to environmental pollution phenomena. Such model, based on the influence diagrams theory, allowed identifying the extremely critical factors, such as wastewater discharges, drainage of diffuse pollution from agriculture and climate changes, which might affect the water quality of the river. The obtained results underlined how the water quality conditions have improved thanks to the continuous controls on the territory, following the application of Water Framework Directive 2000/60/EC. Nevertheless, some fluvial stretches did not reach the “good ecological status” by 2015, because of the increasing population in urban areas recorded in the last years and the high presence of tourists during the summer months, not balanced by a treatment plants upgrade.

Modelling a water purification process for quality monitoring

NARCIS (Netherlands)

Meulen, van der F.H.; Luca, S.; Overal, G.; Dubbeldam, J.L.A.; Di Bucchianico, A.; Jongbloed, G.; Dubbeldam, J.; Groenevelt, W.; Heemink, A.W.; Lahaye, D.; Meerman, C.; Meulen, van der F.

2014-01-01

This paper deals with a quality engineering problem introduced by ‘Waterlaboratorium Noord’ (WLN) situated at the Netherlands. In-terest lies in determining an optimal sampling frequency that provides suÿcient information on the water quality in a drinking water purifica-tion plant. The water

Modeling hydrodynamics, water temperature, and water quality in the Klamath River upstream of Keno Dam, Oregon, 2006-09

Science.gov (United States)

Sullivan, Annett B.; Rounds, Stewart A.; Deas, Michael L.; Asbill, Jessica R.; Wellman, Roy E.; Stewart, Marc A.; Johnston, Matthew W.; Sogutlugil, I. Ertugrul

2011-01-01

A hydrodynamic, water temperature, and water-quality model was constructed for a 20-mile reach of the Klamath River downstream of Upper Klamath Lake, from Link River to Keno Dam, for calendar years 2006-09. The two-dimensional, laterally averaged model CE-QUAL-W2 was used to simulate water velocity, ice cover, water temperature, specific conductance, dissolved and suspended solids, dissolved oxygen, total nitrogen, ammonia, nitrate, total phosphorus, orthophosphate, dissolved and particulate organic matter, and three algal groups. The Link-Keno model successfully simulated the most important spatial and temporal patterns in the measured data for this 4-year time period. The model calibration process provided critical insights into water-quality processes and the nature of those inputs and processes that drive water quality in this reach. The model was used not only to reproduce and better understand water-quality conditions that occurred in 2006-09, but also to test several load-reduction scenarios that have implications for future water-resources management in the river basin. The model construction and calibration process provided results concerning water quality and transport in the Link-Keno reach of the Klamath River, ranging from interesting circulation patterns in the Lake Ewauna area to the nature and importance of organic matter and algae. These insights and results include: * Modeled segment-average water velocities ranged from near 0.0 to 3.0 ft/s in 2006 through 2009. Travel time through the model reach was about 4 days at 2,000 ft3/s and 12 days at 700 ft3/s flow. Flow direction was aligned with the upstream-downstream channel axis for most of the Link-Keno reach, except for Lake Ewauna. Wind effects were pronounced at Lake Ewauna during low-flow conditions, often with circulation in the form of a gyre that rotated in a clockwise direction when winds were towards the southeast and in a counterclockwise direction when winds were towards the northwest

Climate Change Impacts on US Water Quality using two Models: HAWQS and US Basins

Science.gov (United States)

Climate change and freshwater quality are well-linked. Changes in climate result in changes in streamflow and rising water temperatures, which impact biochemical reaction rates and increase stratification in lakes and reservoirs. Using two water quality modeling systems (the Hydr...

Use of tracer to calibrate water quality models in the river Almendares

International Nuclear Information System (INIS)

Dominguez Catasus, Judith; Borroto Portela, Jorge; Perez Machado, Esperanza; Hernandez Garces, Anel

2003-01-01

The Almendares river, one of the most important water bodies of the Havana City, is very polluted. The analysis of parameters as dissolved oxygen and biochemical oxygen demand is very helpful for the studies aimed to the recovery of the river. There is a growing recognition around the word that the water quality models are very useful tools to plan sanitary strategies for the management of wastewater contamination to predict the effectiveness of control options to improve water quality to desired levels. In the present work, the advective, steady- state Streeter and Phelps model was calibrated and validated to simulate the effect of multiple-point and distributed sources on the carbonaceous oxygen demand and dissolved oxygen. The use of the 99mTc and the Rodamine WT as tracers allowed determining the hydrodynamic parameters necessary for modeling purposes

Machine Learning and Deep Learning Models to Predict Runoff Water Quantity and Quality

Science.gov (United States)

Bradford, S. A.; Liang, J.; Li, W.; Murata, T.; Simunek, J.

2017-12-01

Contaminants can be rapidly transported at the soil surface by runoff to surface water bodies. Physically-based models, which are based on the mathematical description of main hydrological processes, are key tools for predicting surface water impairment. Along with physically-based models, data-driven models are becoming increasingly popular for describing the behavior of hydrological and water resources systems since these models can be used to complement or even replace physically based-models. In this presentation we propose a new data-driven model as an alternative to a physically-based overland flow and transport model. First, we have developed a physically-based numerical model to simulate overland flow and contaminant transport (the HYDRUS-1D overland flow module). A large number of numerical simulations were carried out to develop a database containing information about the impact of various input parameters (weather patterns, surface topography, vegetation, soil conditions, contaminants, and best management practices) on runoff water quantity and quality outputs. This database was used to train data-driven models. Three different methods (Neural Networks, Support Vector Machines, and Recurrence Neural Networks) were explored to prepare input- output functional relations. Results demonstrate the ability and limitations of machine learning and deep learning models to predict runoff water quantity and quality.

Propagating Water Quality Analysis Uncertainty Into Resource Management Decisions Through Probabilistic Modeling

Science.gov (United States)

Gronewold, A. D.; Wolpert, R. L.; Reckhow, K. H.

2007-12-01

Most probable number (MPN) and colony-forming-unit (CFU) are two estimates of fecal coliform bacteria concentration commonly used as measures of water quality in United States shellfish harvesting waters. The MPN is the maximum likelihood estimate (or MLE) of the true fecal coliform concentration based on counts of non-sterile tubes in serial dilution of a sample aliquot, indicating bacterial metabolic activity. The CFU is the MLE of the true fecal coliform concentration based on the number of bacteria colonies emerging on a growth plate after inoculation from a sample aliquot. Each estimating procedure has intrinsic variability and is subject to additional uncertainty arising from minor variations in experimental protocol. Several versions of each procedure (using different sized aliquots or different numbers of tubes, for example) are in common use, each with its own levels of probabilistic and experimental error and uncertainty. It has been observed empirically that the MPN procedure is more variable than the CFU procedure, and that MPN estimates are somewhat higher on average than CFU estimates, on split samples from the same water bodies. We construct a probabilistic model that provides a clear theoretical explanation for the observed variability in, and discrepancy between, MPN and CFU measurements. We then explore how this variability and uncertainty might propagate into shellfish harvesting area management decisions through a two-phased modeling strategy. First, we apply our probabilistic model in a simulation-based analysis of future water quality standard violation frequencies under alternative land use scenarios, such as those evaluated under guidelines of the total maximum daily load (TMDL) program. Second, we apply our model to water quality data from shellfish harvesting areas which at present are closed (either conditionally or permanently) to shellfishing, to determine if alternative laboratory analysis procedures might have led to different

Quality assessment and artificial neural networks modeling for characterization of chemical and physical parameters of potable water.

Science.gov (United States)

Salari, Marjan; Salami Shahid, Esmaeel; Afzali, Seied Hosein; Ehteshami, Majid; Conti, Gea Oliveri; Derakhshan, Zahra; Sheibani, Solmaz Nikbakht

2018-04-22

Today, due to the increase in the population, the growth of industry and the variety of chemical compounds, the quality of drinking water has decreased. Five important river water quality properties such as: dissolved oxygen (DO), total dissolved solids (TDS), total hardness (TH), alkalinity (ALK) and turbidity (TU) were estimated by parameters such as: electric conductivity (EC), temperature (T), and pH that could be measured easily with almost no costs. Simulate water quality parameters were examined with two methods of modeling include mathematical and Artificial Neural Networks (ANN). Mathematical methods are based on polynomial fitting with least square method and ANN modeling algorithms are feed-forward networks. All conditions/circumstances covered by neural network modeling were tested for all parameters in this study, except for Alkalinity. All optimum ANN models developed to simulate water quality parameters had precision value as R-value close to 0.99. The ANN model extended to simulate alkalinity with R-value equals to 0.82. Moreover, Surface fitting techniques were used to refine data sets. Presented models and equations are reliable/useable tools for studying water quality parameters at similar rivers, as a proper replacement for traditional water quality measuring equipment's. Copyright © 2018 Elsevier Ltd. All rights reserved.

Industrial pollution and the management of river water quality: a model of Kelani River, Sri Lanka.

Science.gov (United States)

Gunawardena, Asha; Wijeratne, E M S; White, Ben; Hailu, Atakelty; Pandit, Ram

2017-08-19

Water quality of the Kelani River has become a critical issue in Sri Lanka due to the high cost of maintaining drinking water standards and the market and non-market costs of deteriorating river ecosystem services. By integrating a catchment model with a river model of water quality, we developed a method to estimate the effect of pollution sources on ambient water quality. Using integrated model simulations, we estimate (1) the relative contribution from point (industrial and domestic) and non-point sources (river catchment) to river water quality and (2) pollutant transfer coefficients for zones along the lower section of the river. Transfer coefficients provide the basis for policy analyses in relation to the location of new industries and the setting of priorities for industrial pollution control. They also offer valuable information to design socially optimal economic policy to manage industrialized river catchments.

Integrated hydrological and water quality model for river management: A case study on Lena River

Energy Technology Data Exchange (ETDEWEB)

Fonseca, André, E-mail: andrerd@gmail.com; Botelho, Cidália; Boaventura, Rui A.R.; Vilar, Vítor J.P., E-mail: vilar@fe.up.pt

2014-07-01

The Hydrologic Simulation Program FORTRAN (HSPF) model was used to assess the impact of wastewater discharges on the water quality of a Lis River tributary (Lena River), a 176 km{sup 2} watershed in Leiria region, Portugal. The model parameters obtained in this study, could potentially serve as reference values for the calibration of other watersheds in the area or with similar climatic characteristics, which don't have enough data for calibration. Water quality constituents modeled in this study included temperature, fecal coliforms, dissolved oxygen, biochemical oxygen demand, total suspended solids, nitrates, orthophosphates and pH. The results were found to be close to the average observed values for all parameters studied for both calibration and validation periods with percent bias values between − 26% and 23% for calibration and − 30% and 51% for validation for all parameters, with fecal coliforms showing the highest deviation. The model revealed a poor water quality in Lena River for the entire simulation period, according to the Council Directive concerning the surface water quality intended for drinking water abstraction in the Member States (75/440/EEC). Fecal coliforms, orthophosphates and nitrates were found to be 99, 82 and 46% above the limit established in the Directive. HSPF was used to predict the impact of point and nonpoint pollution sources on the water quality of Lena River. Winter and summer scenarios were also addressed to evaluate water quality in high and low flow conditions. A maximum daily load was calculated to determine the reduction needed to comply with the Council Directive 75/440/EEC. The study showed that Lena River is fairly polluted calling for awareness at behavioral change of waste management in order to prevent the escalation of these effects with especially attention to fecal coliforms. - Highlights: • An integrated hydrological and water quality model for river management is presented. • An insight into the

The simple modelling method for storm- and grey-water quality ...

African Journals Online (AJOL)

The simple modelling method for storm- and grey-water quality management applied to Alexandra settlement. ... objectives optimally consist of educational programmes, erosion and sediment control, street sweeping, removal of sanitation system overflows, impervious cover reduction, downspout disconnections, removal of ...

A Hybrid Interval-Robust Optimization Model for Water Quality Management.

Science.gov (United States)

Xu, Jieyu; Li, Yongping; Huang, Guohe

2013-05-01

In water quality management problems, uncertainties may exist in many system components and pollution-related processes ( i.e. , random nature of hydrodynamic conditions, variability in physicochemical processes, dynamic interactions between pollutant loading and receiving water bodies, and indeterminacy of available water and treated wastewater). These complexities lead to difficulties in formulating and solving the resulting nonlinear optimization problems. In this study, a hybrid interval-robust optimization (HIRO) method was developed through coupling stochastic robust optimization and interval linear programming. HIRO can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original chemical oxygen demand (COD) discharge constraints, HIRO enhances the robustness of the optimization processes and resulting solutions. This method was applied to planning of industry development in association with river-water pollution concern in New Binhai District of Tianjin, China. Results demonstrated that the proposed optimization model can effectively communicate uncertainties into the optimization process and generate a spectrum of potential inexact solutions supporting local decision makers in managing benefit-effective water quality management schemes. HIRO is helpful for analysis of policy scenarios related to different levels of economic penalties, while also providing insight into the tradeoff between system benefits and environmental requirements.

A Hybrid Interval–Robust Optimization Model for Water Quality Management

Science.gov (United States)

Xu, Jieyu; Li, Yongping; Huang, Guohe

2013-01-01

Abstract In water quality management problems, uncertainties may exist in many system components and pollution-related processes (i.e., random nature of hydrodynamic conditions, variability in physicochemical processes, dynamic interactions between pollutant loading and receiving water bodies, and indeterminacy of available water and treated wastewater). These complexities lead to difficulties in formulating and solving the resulting nonlinear optimization problems. In this study, a hybrid interval–robust optimization (HIRO) method was developed through coupling stochastic robust optimization and interval linear programming. HIRO can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original chemical oxygen demand (COD) discharge constraints, HIRO enhances the robustness of the optimization processes and resulting solutions. This method was applied to planning of industry development in association with river-water pollution concern in New Binhai District of Tianjin, China. Results demonstrated that the proposed optimization model can effectively communicate uncertainties into the optimization process and generate a spectrum of potential inexact solutions supporting local decision makers in managing benefit-effective water quality management schemes. HIRO is helpful for analysis of policy scenarios related to different levels of economic penalties, while also providing insight into the tradeoff between system benefits and environmental requirements. PMID:23922495

Application of HEC-RAS water quality model to estimate contaminant spreading in small stream

Energy Technology Data Exchange (ETDEWEB)

Halaj, Peter; Bárek, Viliam; Halajová, Anna Báreková; Halajová, Denisa [Slovak University of Agriculture in Nitra, Nitra (Slovakia)

2013-07-01

The paper presents study of some aspects of HEC-RAS water quality model connected to simulation of contaminant transport in small stream. Authors mainly focused on one of the key tasks in process of pollutant transport modelling in streams - determination of the dispersion characteristics represented by longitudinal dispersion coefficient D. Different theoretical and empirical formulas have been proposed for D value determination and they have revealed that the coefficient is variable parameter that depends on hydraulic and morphometric characteristics of the stream reaches. Authors compare the results of several methods of coefficient D assessment, assuming experimental data obtained by tracer studies and compare them with results optimized by HEC-RAS water quality model. The analyses of tracer study and computation outputs allow us to outline the important aspects of longitudinal dispersion coefficient set up in process of the HEC-RAS model use. Key words: longitudinal dispersion coefficient, HEC-RAS, water quality modeling.

Risk-based water resources planning: Coupling water allocation and water quality management under extreme droughts

Science.gov (United States)

Mortazavi-Naeini, M.; Bussi, G.; Hall, J. W.; Whitehead, P. G.

2016-12-01

The main aim of water companies is to have a reliable and safe water supply system. To fulfil their duty the water companies have to consider both water quality and quantity issues and challenges. Climate change and population growth will have an impact on water resources both in terms of available water and river water quality. Traditionally, a distinct separation between water quality and abstraction has existed. However, water quality can be a bottleneck in a system since water treatment works can only treat water if it meets certain standards. For instance, high turbidity and large phytoplankton content can increase sharply the cost of treatment or even make river water unfit for human consumption purposes. It is vital for water companies to be able to characterise the quantity and quality of water under extreme weather events and to consider the occurrence of eventual periods when water abstraction has to cease due to water quality constraints. This will give them opportunity to decide on water resource planning and potential changes to reduce the system failure risk. We present a risk-based approach for incorporating extreme events, based on future climate change scenarios from a large ensemble of climate model realisations, into integrated water resources model through combined use of water allocation (WATHNET) and water quality (INCA) models. The annual frequency of imposed restrictions on demand is considered as measure of reliability. We tested our approach on Thames region, in the UK, with 100 extreme events. The results show increase in frequency of imposed restrictions when water quality constraints were considered. This indicates importance of considering water quality issues in drought management plans.

Water quality management for Lake Mariout

Directory of Open Access Journals (Sweden)

N. Donia

2016-06-01

Full Text Available A hydrodynamic and water quality model was used to study the current status of the Lake Mariout subject to the pollution loadings from the agricultural drains and the point sources discharging directly to the Lake. The basic water quality modelling component simulates the main water quality parameters including the oxygen compounds (BOD, COD, DO, nutrients compounds (NH4, TN, TP, and finally the temperature, salinity and inorganic matter. Many scenarios have been conducted to improve the circulation and the water quality in the lake and to assess the spreading and mixing of the discharge effluents and its impact on the water quality of the main basin. Several pilot interventions were applied through the model in the Lake Mariout together with the upgrades of the East and West Waste Water Treatment Plants in order to achieve at least 5% reduction in the pollution loads entering the Mediterranean Sea through Lake Mariout in order to improve the institutional mechanisms for sustainable coastal zone management in Alexandria in particular to reduce land-based pollution to the Mediterranean Sea.

[Development and application of a multi-species water quality model for water distribution systems with EPANET-MSX].

Science.gov (United States)

Sun, Fu; Chen, Ji-ning; Zeng, Si-yu

2008-12-01

A conceptual multi-species water quality model for water distribution systems was developed on the basis of the toolkit of the EPANET-MSX software. The model divided the pipe segment into four compartments including pipe wall, biofilm, boundary layer and bulk liquid. The involved processes were substrate utilization and microbial growth, decay and inactivation of microorganisms, mass transfer of soluble components through the boundary layer, adsorption and desorption of particular components between bulk liquid and biofilm, oxidation and halogenation of organic matter by residual chlorine, and chlorine consumption by pipe wall. The fifteen simulated variables included the seven common variables both in the biofilm and in the bulk liquid, i.e. soluble organic matter, particular organic matter, ammonia nitrogen, residual chlorine, heterotrophic bacteria, autotrophic bacteria and inert solids, as well as biofilm thickness on the pipe wall. The model was validated against the data from a series of pilot experiments, and the simulation accuracy for residual chlorine and turbidity were 0.1 mg/L and 0.3 NTU respectively. A case study showed that the model could reasonably reflect the dynamic variation of residual chlorine and turbidity in the studied water distribution system, while Monte Carlo simulation, taking into account both the variability of finished water from the waterworks and the uncertainties of model parameters, could be performed to assess the violation risk of water quality in the water distribution system.

A review on integration of artificial intelligence into water quality modelling.

Science.gov (United States)

Chau, Kwok-wing

2006-07-01

With the development of computing technology, numerical models are often employed to simulate flow and water quality processes in coastal environments. However, the emphasis has conventionally been placed on algorithmic procedures to solve specific problems. These numerical models, being insufficiently user-friendly, lack knowledge transfers in model interpretation. This results in significant constraints on model uses and large gaps between model developers and practitioners. It is a difficult task for novice application users to select an appropriate numerical model. It is desirable to incorporate the existing heuristic knowledge about model manipulation and to furnish intelligent manipulation of calibration parameters. The advancement in artificial intelligence (AI) during the past decade rendered it possible to integrate the technologies into numerical modelling systems in order to bridge the gaps. The objective of this paper is to review the current state-of-the-art of the integration of AI into water quality modelling. Algorithms and methods studied include knowledge-based system, genetic algorithm, artificial neural network, and fuzzy inference system. These techniques can contribute to the integrated model in different aspects and may not be mutually exclusive to one another. Some future directions for further development and their potentials are explored and presented.

Development of wavelet-ANN models to predict water quality parameters in Hilo Bay, Pacific Ocean.

Science.gov (United States)

Alizadeh, Mohamad Javad; Kavianpour, Mohamad Reza

2015-09-15

The main objective of this study is to apply artificial neural network (ANN) and wavelet-neural network (WNN) models for predicting a variety of ocean water quality parameters. In this regard, several water quality parameters in Hilo Bay, Pacific Ocean, are taken under consideration. Different combinations of water quality parameters are applied as input variables to predict daily values of salinity, temperature and DO as well as hourly values of DO. The results demonstrate that the WNN models are superior to the ANN models. Also, the hourly models developed for DO prediction outperform the daily models of DO. For the daily models, the most accurate model has R equal to 0.96, while for the hourly model it reaches up to 0.98. Overall, the results show the ability of the model to monitor the ocean parameters, in condition with missing data, or when regular measurement and monitoring are impossible. Copyright © 2015 Elsevier Ltd. All rights reserved.

Application of regression model on stream water quality parameters

International Nuclear Information System (INIS)

Suleman, M.; Maqbool, F.; Malik, A.H.; Bhatti, Z.A.

2012-01-01

Statistical analysis was conducted to evaluate the effect of solid waste leachate from the open solid waste dumping site of Salhad on the stream water quality. Five sites were selected along the stream. Two sites were selected prior to mixing of leachate with the surface water. One was of leachate and other two sites were affected with leachate. Samples were analyzed for pH, water temperature, electrical conductivity (EC), total dissolved solids (TDS), Biological oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO) and total bacterial load (TBL). In this study correlation coefficient r among different water quality parameters of various sites were calculated by using Pearson model and then average of each correlation between two parameters were also calculated, which shows TDS and EC and pH and BOD have significantly increasing r value, while temperature and TDS, temp and EC, DO and BL, DO and COD have decreasing r value. Single factor ANOVA at 5% level of significance was used which shows EC, TDS, TCL and COD were significantly differ among various sites. By the application of these two statistical approaches TDS and EC shows strongly positive correlation because the ions from the dissolved solids in water influence the ability of that water to conduct an electrical current. These two parameters significantly vary among 5 sites which are further confirmed by using linear regression. (author)

Water-quality models to assess algal community dynamics, water quality, and fish habitat suitability for two agricultural land-use dominated lakes in Minnesota, 2014

Science.gov (United States)

Smith, Erik A.; Kiesling, Richard L.; Ziegeweid, Jeffrey R.

2017-07-20

Fish habitat can degrade in many lakes due to summer blue-green algal blooms. Predictive models are needed to better manage and mitigate loss of fish habitat due to these changes. The U.S. Geological Survey (USGS), in cooperation with the Minnesota Department of Natural Resources, developed predictive water-quality models for two agricultural land-use dominated lakes in Minnesota—Madison Lake and Pearl Lake, which are part of Minnesota’s sentinel lakes monitoring program—to assess algal community dynamics, water quality, and fish habitat suitability of these two lakes under recent (2014) meteorological conditions. The interaction of basin processes to these two lakes, through the delivery of nutrient loads, were simulated using CE-QUAL-W2, a carbon-based, laterally averaged, two-dimensional water-quality model that predicts distribution of temperature and oxygen from interactions between nutrient cycling, primary production, and trophic dynamics.The CE-QUAL-W2 models successfully predicted water temperature and dissolved oxygen on the basis of the two metrics of mean absolute error and root mean square error. For Madison Lake, the mean absolute error and root mean square error were 0.53 and 0.68 degree Celsius, respectively, for the vertical temperature profile comparisons; for Pearl Lake, the mean absolute error and root mean square error were 0.71 and 0.95 degree Celsius, respectively, for the vertical temperature profile comparisons. Temperature and dissolved oxygen were key metrics for calibration targets. These calibrated lake models also simulated algal community dynamics and water quality. The model simulations presented potential explanations for persistently large total phosphorus concentrations in Madison Lake, key differences in nutrient concentrations between these lakes, and summer blue-green algal bloom persistence.Fish habitat suitability simulations for cool-water and warm-water fish indicated that, in general, both lakes contained a large

Identifying the Correlation between Water Quality Data and LOADEST Model Behavior in Annual Sediment Load Estimations

Directory of Open Access Journals (Sweden)

Youn Shik Park

2016-08-01

Full Text Available Water quality samples are typically collected less frequently than flow since water quality sampling is costly. Load Estimator (LOADEST, provided by the United States Geological Survey, is used to predict water quality concentration (or load on days when flow data are measured so that the water quality data are sufficient for annual pollutant load estimation. However, there is a need to identify water quality data requirements for accurate pollutant load estimation. Measured daily sediment data were collected from 211 streams. Estimated annual sediment loads from LOADEST and subsampled data were compared to the measured annual sediment loads (true load. The means of flow for calibration data were correlated to model behavior. A regression equation was developed to compute the required mean of flow in calibration data to best calibrate the LOADEST regression model coefficients. LOADEST runs were performed to investigate the correlation between the mean flow in calibration data and model behaviors as daily water quality data were subsampled. LOADEST calibration data used sediment concentration data for flows suggested by the regression equation. Using the mean flow calibrated by the regression equation reduced errors in annual sediment load estimation from −39.7% to −10.8% compared to using all available data.

Water Quality Analysis Simulation Program (WASP)

Science.gov (United States)

The Water Quality Analysis Simulation Program (WASP) model helps users interpret and predict water quality responses to natural phenomena and manmade pollution for various pollution management decisions.

Modelling spatial and temporal variations in the water quality of an artificial water reservoir in the semiarid Midwest of Argentina

Energy Technology Data Exchange (ETDEWEB)

Cid, Fabricio D., E-mail: fabricio.cid@gmail.com [Laboratory of Biology ' Prof. E. Caviedes Codelia' , Facultad de Ciencias Humanas, Universidad Nacional de San Luis, San Luis (Argentina); Laboratory of Integrative Biology, Institute for Multidisciplinary Research in Biology (IMIBIO-SL), Consejo Nacional de Investigaciones Cientificas y Tecnicas, San Luis (Argentina); Department of Biochemistry and Biological Sciences, Facultad de Quimica, Bioquimica y Farmacia, Universidad Nacional de San Luis, San Luis (Argentina); Anton, Rosa I. [Department of Analytical Chemistry, Facultad de Quimica, Bioquimica y Farmacia, Universidad Nacional de San Luis, San Luis (Argentina); Pardo, Rafael; Vega, Marisol [Department of Analytical Chemistry, Facultad de Ciencias, Universidad de Valladolid, Valladolid (Spain); Caviedes-Vidal, Enrique [Laboratory of Biology ' Prof. E. Caviedes Codelia' , Facultad de Ciencias Humanas, Universidad Nacional de San Luis, San Luis (Argentina); Laboratory of Integrative Biology, Institute for Multidisciplinary Research in Biology (IMIBIO-SL), Consejo Nacional de Investigaciones Cientificas y Tecnicas, San Luis (Argentina); Department of Biochemistry and Biological Sciences, Facultad de Quimica, Bioquimica y Farmacia, Universidad Nacional de San Luis, San Luis (Argentina)

2011-10-31

Highlights: {yields} Water quality of an Argentinean reservoir has been investigated by N-way PCA. {yields} PARAFAC mode modelled spatial and seasonal variations of water composition. {yields} Two factors related with organic and lead pollution have been identified. {yields} The most polluted areas of the reservoir were located, and polluting sources identified. - Abstract: Temporal and spatial patterns of water quality of an important artificial water reservoir located in the semiarid Midwest of Argentina were investigated using chemometric techniques. Surface water samples were collected at 38 points of the water reservoir during eleven sampling campaigns between October 1998 and June 2000, covering the warm wet season and the cold dry season, and analyzed for dissolved oxygen (DO), conductivity, pH, ammonium, nitrate, nitrite, total dissolved solids (TDS), alkalinity, hardness, bicarbonate, chloride, sulfate, calcium, magnesium, fluoride, sodium, potassium, iron, aluminum, silica, phosphate, sulfide, arsenic, chromium, lead, cadmium, chemical oxygen demand (COD), biochemical oxygen demand (BOD), viable aerobic bacteria (VAB) and total coliform bacteria (TC). Concentrations of lead, ammonium, nitrite and coliforms were higher than the maximum allowable limits for drinking water in a large proportion of the water samples. To obtain a general representation of the spatial and temporal trends of the water quality parameters at the reservoir, the three-dimensional dataset (sampling sites x parameters x sampling campaigns) has been analyzed by matrix augmentation principal component analysis (MA-PCA) and N-way principal component analysis (N-PCA) using Tucker3 and PARAFAC (Parallel Factor Analysis) models. MA-PCA produced a component accounting for the general behavior of parameters associated with organic pollution. The Tucker3 models were not appropriate for modelling the water quality dataset. The two-factor PARAFAC model provided the best picture to understand the

Modelling spatial and temporal variations in the water quality of an artificial water reservoir in the semiarid Midwest of Argentina

International Nuclear Information System (INIS)

Cid, Fabricio D.; Anton, Rosa I.; Pardo, Rafael; Vega, Marisol; Caviedes-Vidal, Enrique

2011-01-01

Highlights: → Water quality of an Argentinean reservoir has been investigated by N-way PCA. → PARAFAC mode modelled spatial and seasonal variations of water composition. → Two factors related with organic and lead pollution have been identified. → The most polluted areas of the reservoir were located, and polluting sources identified. - Abstract: Temporal and spatial patterns of water quality of an important artificial water reservoir located in the semiarid Midwest of Argentina were investigated using chemometric techniques. Surface water samples were collected at 38 points of the water reservoir during eleven sampling campaigns between October 1998 and June 2000, covering the warm wet season and the cold dry season, and analyzed for dissolved oxygen (DO), conductivity, pH, ammonium, nitrate, nitrite, total dissolved solids (TDS), alkalinity, hardness, bicarbonate, chloride, sulfate, calcium, magnesium, fluoride, sodium, potassium, iron, aluminum, silica, phosphate, sulfide, arsenic, chromium, lead, cadmium, chemical oxygen demand (COD), biochemical oxygen demand (BOD), viable aerobic bacteria (VAB) and total coliform bacteria (TC). Concentrations of lead, ammonium, nitrite and coliforms were higher than the maximum allowable limits for drinking water in a large proportion of the water samples. To obtain a general representation of the spatial and temporal trends of the water quality parameters at the reservoir, the three-dimensional dataset (sampling sites x parameters x sampling campaigns) has been analyzed by matrix augmentation principal component analysis (MA-PCA) and N-way principal component analysis (N-PCA) using Tucker3 and PARAFAC (Parallel Factor Analysis) models. MA-PCA produced a component accounting for the general behavior of parameters associated with organic pollution. The Tucker3 models were not appropriate for modelling the water quality dataset. The two-factor PARAFAC model provided the best picture to understand the spatial and

Use of Nutrient Balances in Comprehensive Watershed Water Quality Modeling of Chesapeake Bay

National Research Council Canada - National Science Library

Donigian, Anthony

1998-01-01

... state of-the-art watershed modeling capability that includes detailed soil process simulation for agricultural areas, linked to an instream water quality and nutrient model capable of representing...

Development of Water Quality Forecasting Models Based on the SOM-ANN on TMDL Unit Watershed in Nakdong River

Science.gov (United States)

KIM, M.; Kim, J.; Baek, J.; Kim, C.; Shin, H.

2013-12-01

It has being happened as flush flood or red/green tide in various natural phenomena due to climate change and indiscreet development of river or land. Especially, water being very important to man should be protected and managed from water quality pollution, and in water resources management, real-time watershed monitoring system is being operated with the purpose of keeping watch and managing on rivers. It is especially important to monitor and forecast water quality in watershed. A study area selected Nak_K as one site among TMDL unit watershed in Nakdong River. This study is to develop a water quality forecasting model connected with making full use of observed data of 8 day interval from Nakdong River Environment Research Center. When forecasting models for each of the BOD, DO, COD, and chlorophyll-a are established considering correlation of various water quality factors, it is needed to select water quality factors showing highly considerable correlation with each water quality factor which is BOD, DO, COD, and chlorophyll-a. For analyzing the correlation of the factors (reservoir discharge, precipitation, air temperature, DO, BOD, COD, Tw, TN, TP, chlorophyll-a), in this study, self-organizing map was used and cross correlation analysis method was also used for comparing results drawn. Based on the results, each forecasting model for BOD, DO, COD, and chlorophyll-a was developed during the short period as 8, 16, 24, 32 days at 8 day interval. The each forecasting model is based on neural network with back propagation algorithm. That is, the study is connected with self-organizing map for analyzing correlation among various factors and neural network model for forecasting of water quality. It is considerably effective to manage the water quality in plenty of rivers, then, it specially is possible to monitor a variety of accidents in water quality. It will work well to protect water quality and to prevent destruction of the environment becoming more and more

Hydrodynamics and water quality models applied to Sepetiba Bay

Science.gov (United States)

Cunha, Cynara de L. da N.; Rosman, Paulo C. C.; Ferreira, Aldo Pacheco; Carlos do Nascimento Monteiro, Teófilo

2006-10-01

A coupled hydrodynamic and water quality model is used to simulate the pollution in Sepetiba Bay due to sewage effluent. Sepetiba Bay has a complicated geometry and bottom topography, and is located on the Brazilian coast near Rio de Janeiro. In the simulation, the dissolved oxygen (DO) concentration and biochemical oxygen demand (BOD) are used as indicators for the presence of organic matter in the body of water, and as parameters for evaluating the environmental pollution of the eastern part of Sepetiba Bay. Effluent sources in the model are taken from DO and BOD field measurements. The simulation results are consistent with field observations and demonstrate that the model has been correctly calibrated. The model is suitable for evaluating the environmental impact of sewage effluent on Sepetiba Bay from river inflows, assessing the feasibility of different treatment schemes, and developing specific monitoring activities. This approach has general applicability for environmental assessment of complicated coastal bays.

Using a Content Management System for Integrated Water Quantity, Quality and Instream Flows Modeling

Science.gov (United States)

Burgholzer, R.; Brogan, C. O.; Scott, D.; Keys, T.

2017-12-01

With increased population and water demand, in-stream flows can become depleted by consumptive uses and dilution of permitted discharges may be compromised. Reduced flows downstream of water withdrawals may increase the violation rate of bacterial concentrations from direct deposition by livestock and wildlife. Water storage reservoirs are constructed and operated to insure more stable supplies for consumptive demands and dilution flows, however their use comes at the cost of increased evaporative losses, potential for thermal pollution, interrupted fish migration, and reduced flooding events that are critical to maintain habitat and water quality. Due to this complex interrelationship between water quantity, quality and instream habitat comprehensive multi-disciplinary models must be developed to insure long-term sustainability of water resources and to avoid conflicts between drinking water, food and energy production, and aquatic biota. The Commonwealth of Virginia funded the expansion of the Chesapeake Bay Program Phase 5 model to cover the entire state, and has been using this model to evaluate water supply permit and planning since 2009. This integrated modeling system combines a content management system (Drupal and PHP) for model input data and leverages the modularity of HSPF with the custom segmentation and parameterization routines programmed by modelers working with the Chesapeake Bay Program. The model has been applied to over 30 Virginia Water Permits, instream flows and aquatic habitat models and a Virginias 30 year water supply demand projections. Future versions will leverage the Bay Model auto-calibration routines for adding small-scale water supply and TMDL models, utilize climate change scenarios, and integrate Virginia's reservoir management modules into the Chesapeake Bay watershed model, feeding projected demand and operational changes back up to EPA models to improve the realism of future Bay-wide simulations.

Using Water Quality Models in Management - A Multiple Model Assessment, Analysis of Confidence, and Evaluation of Climate Change Impacts

Science.gov (United States)

Irby, Isaac David

Human impacts on the Chesapeake Bay through increased nutrient run-off as a result of land-use change, urbanization, and industrialization, have resulted in a degradation of water quality over the last half-century. These direct impacts, compounded with human-induced climate changes such as warming, rising sea-level, and changes in precipitation, have elevated the conversation surrounding the future of water quality in the Bay. The overall goal of this dissertation project is to use a combination of models and data to better understand and quantify the impact of changes in nutrient loads and climate on water quality in the Chesapeake Bay. This research achieves that goal in three parts. First, a set of eight water quality models is used to establish a model mean and assess model skill. All models were found to exhibit similar skill in resolving dissolved oxygen concentrations as well as a number of dissolved oxygen-influencing variables (temperature, salinity, stratification, chlorophyll and nitrate) and the model mean exhibited the highest individual skill. The location of stratification within the water column was found to be a limiting factor in the models' ability to adequately simulate habitat compression resulting from low-oxygen conditions. Second, two of the previous models underwent the regulatory Chesapeake Bay pollution diet mandated by the Environmental Protection Agency. Both models exhibited a similar relative improvement in dissolved oxygen concentrations as a result of the reduction of nutrients stipulated in the pollution diet. A Confidence Index was developed to identify the locations of the Bay where the models are in agreement and disagreement regarding the impacts of the pollution diet. The models were least certain in the deep part of the upper main stem of the Bay and the uncertainty primarily stemmed from the post-processing methodology. Finally, by projecting the impacts of climate change in 2050 on the Bay, the potential success of the

Urban Hydrology and Water Quality Modeling - Resolution Modeling Comparison for Water Quantity and Quality

Science.gov (United States)

Fry, T. J.; Maxwell, R. M.

2014-12-01

Urbanization presents challenging water resource problems for communities worldwide. The hydromodifications associated with urbanization results in increased runoff rates and volumes and increased peak flows. These hydrologic changes can lead to increased erosion and stream destabilization, decreased evapotranspiration, decreased ground water recharge, increases in pollutant loading, and localized anthropogenic climate change or Urban Heat Islands. Stormwater represents a complex and dynamic component of the urban water cycle that requires careful mitigation. With the implementation of Phase II rules under the CWA, stormwater management is shifting from a drainage-efficiency focus to a natural systems focus. The natural system focus, referred to as Low Impact Development (LID), or Green Infrastructure, uses best management practices (BMPs) to reduce the impacts caused by urbanization hydromodification. Large-scale patterns of stormwater runoff from urban environments are complex and it is unclear what the large-scale impacts of green infrastructure are on the water cycle. High resolution physically based hydrologic models can be used to more accurately simulate the urban hydrologic cycle. These types of models tend to be more dynamic and allow for greater flexibility in evaluating and accounting for various hydrologic processes in the urban environment that may be lost with lower resolution conceptual models. We propose to evaluate the effectiveness of high resolution models to accurately represent and determine the urban hydrologic cycle with the overall goal of being able to accurately assess the impacts of LID BMPs in urban environments. We propose to complete a rigorous model intercomparison between ParFlow and FLO-2D. Both of these models can be scaled to higher resolutions, allow for rainfall to be spatially and temporally input, and solve the shallow water equations. Each model is different in the way it accounts for infiltration, initial abstraction losses

Forecasting Models for Some Water Quality Parameters of Shatt Al-Hilla River, Iraq

Directory of Open Access Journals (Sweden)

Rafa H. Al-Suhili

2017-07-01

Full Text Available This paper provides Artificial Neural Networks model versions for forecasting the monthly averages of some chemical water quality parameters of Shatt Al-Hilla River, which is located at Hilla City, south of Iraq. The water quality parameters investigated were Sulphate, Magnesium, Calcium, Alkalinity, and Total Hardness. Results indicate that for Sulphate and Calcium high correlation coefficients models were observed to be (0.9 and 0.88, while for Magnesium, Alkalinity and Hardness low correlation coefficients model were observed to be (0.48,0.58, and 0.51 respectively. Serial correlation behavior of these variables indicate at that high lag time correlations sequences are observed for the first two variables and low ones for the last three water quality parameters. A serial correlation coefficient analysis was done and indicates that as the variable exhibited weak lag correlation structure, then a successful ANN forecasting model could not be obtained even if many trials were done to enhance it's performance, such as increasing the number of nodes, the lagged input variables, and/or changing the learning rate and the momentum term values, or the use of different types of activation functions. On the other hand, those variables that have a strong lag correlation structure can easily fit successful ANN forecasting models

Estimation of contribution ratios of pollutant sources to a specific section based on an enhanced water quality model.

Science.gov (United States)

Cao, Bibo; Li, Chuan; Liu, Yan; Zhao, Yue; Sha, Jian; Wang, Yuqiu

2015-05-01

Because water quality monitoring sections or sites could reflect the water quality status of rivers, surface water quality management based on water quality monitoring sections or sites would be effective. For the purpose of improving water quality of rivers, quantifying the contribution ratios of pollutant resources to a specific section is necessary. Because physical and chemical processes of nutrient pollutants are complex in water bodies, it is difficult to quantitatively compute the contribution ratios. However, water quality models have proved to be effective tools to estimate surface water quality. In this project, an enhanced QUAL2Kw model with an added module was applied to the Xin'anjiang Watershed, to obtain water quality information along the river and to assess the contribution ratios of each pollutant source to a certain section (the Jiekou state-controlled section). Model validation indicated that the results were reliable. Then, contribution ratios were analyzed through the added module. Results show that among the pollutant sources, the Lianjiang tributary contributes the largest part of total nitrogen (50.43%), total phosphorus (45.60%), ammonia nitrogen (32.90%), nitrate (nitrite + nitrate) nitrogen (47.73%), and organic nitrogen (37.87%). Furthermore, contribution ratios in different reaches varied along the river. Compared with pollutant loads ratios of different sources in the watershed, an analysis of contribution ratios of pollutant sources for each specific section, which takes the localized chemical and physical processes into consideration, was more suitable for local-regional water quality management. In summary, this method of analyzing the contribution ratios of pollutant sources to a specific section based on the QUAL2Kw model was found to support the improvement of the local environment.

Application of water quality models to rivers in Johor

Science.gov (United States)

Chii, Puah Lih; Rahman, Haliza Abd.

2017-08-01

River pollution is one the most common hazard in many countries in the world, which includes Malaysia. Many rivers have been polluted because of the rapid growth in industrialization to support the country's growing population and economy. Domestic and industrial sewage, agricultural wastes have polluted the rivers and will affect the water quality. Based on the Malaysia Environment Quality Report 2007, the Department of Environment (DOE) has described that one of the major pollutants is Biochemical Oxygen Demand (BOD). Data from DOE in 2004, based on BOD, 18 river basins were classified polluted, 37 river basins were slightly polluted and 65 river basins were in clean condition. In this paper, two models are fitted the data of rivers in Johor state namely Streeter-Phelps model and nonlinear regression (NLR) model. The BOD concentration data for the two rivers in Johor state from year 1981 to year 1990 is analyzed. To estimate the parameters for the Streeter-Phelps model and NLR model, this study focuses on the weighted least squares and Gauss-Newton method respectively. Based on the value of Mean Square Error, NLR model is a better model compared to Streeter-Phelps model.

Bio-economic modeling of water quality improvements using a dynamic applied general equilibrium approach

NARCIS (Netherlands)

Dellink, R.; Brouwer, R.; Linderhof, V.G.M.; Stone, K.

2011-01-01

An integrated bio-economic model is developed to assess the impacts of pollution reduction policies on water quality and the economy. Emission levels of economic activities to water are determined based on existing environmental accounts. These emission levels are built into a dynamic economic model

Refining models for quantifying the water quality benefits of improved animal management for use in water quality trading

Science.gov (United States)

Water quality trading (WQT) is a market-based approach that allows point sources of water pollution to meet their water quality obligations by purchasing credits from the reduced discharges from other point or nonpoint sources. Non-permitted animal operations and fields of permitted animal operatio...

MATHEMATICAL MODEL FOR THE SIMULATION OF WATER QUALITY IN RIVERS USING THE VENSIM PLE® SOFTWARE

Directory of Open Access Journals (Sweden)

Julio Cesar de S. I. Gonçalves

2013-06-01

Full Text Available Mathematical modeling of water quality in rivers is an important tool for the planning and management of water resources. Nevertheless, the available models frequently show structural and functional limitations. With the objective of reducing these drawbacks, a new model has been developed to simulate water quality in rivers under unsteady conditions; this model runs on the Vensim PLE® software and can also be operated for steady-state conditions. The following eighteen water quality variables can be simulated: DO, BODc, organic nitrogen (No, ammonia nitrogen (Na, nitrite (Ni, nitrate (Nn, organic and inorganic phosphorus (Fo and Fi, respectively, inorganic solids (Si, phytoplankton (F, zooplankton (Z, bottom algae (A, detritus (D, total coliforms (TC, alkalinity (Al., total inorganic carbon (TIC, pH, and temperature (T. Methane as well as nitrogen and phosphorus compounds that are present in the aerobic and anaerobic layers of the sediment can also be simulated. Several scenarios were generated for computational simulations produced using the new model by using the QUAL2K program, and, when possible, analytical solutions. The results obtained using the new model strongly supported the results from the QUAL family and analytical solutions.

Evaluation of global water quality - the potential of a data- and model-driven analysis

Science.gov (United States)

Bärlund, Ilona; Flörke, Martina; Alcamo, Joseph; Völker, Jeanette; Malsy, Marcus; Kaus, Andrew; Reder, Klara; Büttner, Olaf; Katterfeld, Christiane; Dietrich, Désirée; Borchardt, Dietrich

2016-04-01

The ongoing socio-economic development presents a new challenge for water quality worldwide, especially in developing and emerging countries. It is estimated that due to population growth and the extension of water supply networks, the amount of waste water will rise sharply. This can lead to an increased risk of surface water quality degradation, if the wastewater is not sufficiently treated. This development has impacts on ecosystems and human health, as well as food security. The United Nations Member States have adopted targets for sustainable development. They include, inter alia, sustainable protection of water quality and sustainable use of water resources. To achieve these goals, appropriate monitoring strategies and the development of indicators for water quality are required. Within the pre-study for a 'World Water Quality Assessment' (WWQA) led by United Nations Environment Programme (UNEP), a methodology for assessing water quality, taking into account the above-mentioned objectives has been developed. The novelty of this methodology is the linked model- and data-driven approach. The focus is on parameters reflecting the key water quality issues, such as increased waste water pollution, salinization or eutrophication. The results from the pre-study show, for example, that already about one seventh of all watercourses in Latin America, Africa and Asia show high organic pollution. This is of central importance for inland fisheries and associated food security. In addition, it could be demonstrated that global water quality databases have large gaps. These must be closed in the future in order to obtain an overall picture of global water quality and to target measures more efficiently. The aim of this presentation is to introduce the methodology developed within the WWQA pre-study and to show selected examples of application in Latin America, Africa and Asia.

Conceptual design of a regional water quality screening model. [RFF; Reach; HANFORD; ARQUAL; SEAS; NASQUAN

Energy Technology Data Exchange (ETDEWEB)

Davis, M J

1981-01-01

This water quality assessment methodology is intended to predict concentrations at future times and to estimate the impacts on water quality of energy-related activities (including industrial boilers). Estimates of impacts on water quality at future times are based on incremental changes in pollutant inputs to the body water. Important features of the model are: use of measured concentrations to account for existing conditions; consideration of incremental changes in pollutant loads; emphasis on the energy sector and industrial boilers; analysis restricted to streams only; no attempt to fully account for pollutant behavior; and flexible design, so that future improvements can be incorporated. The basic approach is very similar to the one used by Argonne's ARQUAL model but will allow more complex pollutant behavior and more flexibility in use. (PSB)

Satellite remote sensing for modeling and monitoring of water quality in the Great Lakes

Science.gov (United States)

Coffield, S. R.; Crosson, W. L.; Al-Hamdan, M. Z.; Barik, M. G.

2017-12-01

Consistent and accurate monitoring of the Great Lakes is critical for protecting the freshwater ecosystems, quantifying the impacts of climate change, understanding harmful algal blooms, and safeguarding public health for the millions who rely on the Lakes for drinking water. While ground-based monitoring is often hampered by limited sampling resolution, satellite data provide surface reflectance measurements at much more complete spatial and temporal scales. In this study, we implemented NASA data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Aqua satellite to build robust water quality models. We developed and validated models for chlorophyll-a, nitrogen, phosphorus, and turbidity based on combinations of the six MODIS Ocean Color bands (412, 443, 488, 531, 547, and 667nm) for 2003-2016. Second, we applied these models to quantify trends in water quality through time and in relation to changing land cover, runoff, and climate for six selected coastal areas in Lakes Michigan and Erie. We found strongest models for chlorophyll-a in Lake Huron (R2 = 0.75), nitrogen in Lake Ontario (R2=0.66), phosphorus in Lake Erie (R2=0.60), and turbidity in Lake Erie (R2=0.86). These offer improvements over previous efforts to model chlorophyll-a while adding nitrogen, phosphorus, and turbidity. Mapped water quality parameters showed high spatial variability, with nitrogen concentrated largely in Superior and coastal Michigan and high turbidity, phosphorus, and chlorophyll near urban and agricultural areas of Erie. Temporal analysis also showed concurrence of high runoff or precipitation and nitrogen in Lake Michigan offshore of wetlands, suggesting that water quality in these areas is sensitive to changes in climate.

Some Remarks on the Calibration and Validation of Numerical Water Quality Models

DEFF Research Database (Denmark)

Larsen, Torben

1997-01-01

It is a general experience that complete deterministic water quality models for aquatic systems most often show surprisingly poor agreement when it comes to comparison between model estimates and measurement in the actual system. Often this discrepancy is misunderstood as a lack of complexity and...

An integrated system dynamics model developed for managing lake water quality at the watershed scale.

Science.gov (United States)

Liu, Hui; Benoit, Gaboury; Liu, Tao; Liu, Yong; Guo, Huaicheng

2015-05-15

A reliable system simulation to relate socioeconomic development with water environment and to comprehensively represent a watershed's dynamic features is important. In this study, after identifying lake watershed system processes, we developed a system dynamics modeling framework for managing lake water quality at the watershed scale. Two reinforcing loops (Development and Investment Promotion) and three balancing loops (Pollution, Resource Consumption, and Pollution Control) were constituted. Based on this work, we constructed Stock and Flow Diagrams that embedded a pollutant load model and a lake water quality model into a socioeconomic system dynamics model. The Dianchi Lake in Yunnan Province, China, which is the sixth largest and among the most severely polluted freshwater lakes in China, was employed as a case study to demonstrate the applicability of the model. Water quality parameters considered in the model included chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP). The business-as-usual (BAU) scenario and three alternative management scenarios on spatial adjustment of industries and population (S1), wastewater treatment capacity construction (S2), and structural adjustment of agriculture (S3), were simulated to assess the effectiveness of certain policies in improving water quality. Results showed that S2 is most effective scenario, and the COD, TN, and TP concentrations in Caohai in 2030 are 52.5, 10.9, and 0.8 mg/L, while those in Waihai are 9.6, 1.2, and 0.08 mg/L, with sustained development in the watershed. Thus, the model can help support the decision making required in development and environmental protection strategies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Assessing the effects of regional payment for watershed services program on water quality using an intervention analysis model.

Science.gov (United States)

Lu, Yan; He, Tian

2014-09-15

Much attention has been recently paid to ex-post assessments of socioeconomic and environmental benefits of payment for ecosystem services (PES) programs on poverty reduction, water quality, and forest protection. To evaluate the effects of a regional PES program on water quality, we selected chemical oxygen demand (COD) and ammonia-nitrogen (NH3-N) as indicators of water quality. Statistical methods and an intervention analysis model were employed to assess whether the PES program produced substantial changes in water quality at 10 water-quality sampling stations in the Shaying River watershed, China during 2006-2011. Statistical results from paired-sample t-tests and box plots of COD and NH3-N concentrations at the 10 stations showed that the PES program has played a positive role in improving water quality and reducing trans-boundary water pollution in the Shaying River watershed. Using the intervention analysis model, we quantitatively evaluated the effects of the intervention policy, i.e., the watershed PES program, on water quality at the 10 stations. The results suggest that this method could be used to assess the environmental benefits of watershed or water-related PES programs, such as improvements in water quality, seasonal flow regulation, erosion and sedimentation, and aquatic habitat. Copyright © 2014 Elsevier B.V. All rights reserved.

Proactive modeling of water quality impacts of extreme precipitation events in a drinking water reservoir.

Science.gov (United States)

Jeznach, Lillian C; Hagemann, Mark; Park, Mi-Hyun; Tobiason, John E

2017-10-01

Extreme precipitation events are of concern to managers of drinking water sources because these occurrences can affect both water supply quantity and quality. However, little is known about how these low probability events impact organic matter and nutrient loads to surface water sources and how these loads may impact raw water quality. This study describes a method for evaluating the sensitivity of a water body of interest from watershed input simulations under extreme precipitation events. An example application of the method is illustrated using the Wachusett Reservoir, an oligo-mesotrophic surface water reservoir in central Massachusetts and a major drinking water supply to metropolitan Boston. Extreme precipitation event simulations during the spring and summer resulted in total organic carbon, UV-254 (a surrogate measurement for reactive organic matter), and total algae concentrations at the drinking water intake that exceeded recorded maximums. Nutrient concentrations after storm events were less likely to exceed recorded historical maximums. For this particular reservoir, increasing inter-reservoir transfers of water with lower organic matter content after a large precipitation event has been shown in practice and in model simulations to decrease organic matter levels at the drinking water intake, therefore decreasing treatment associated oxidant demand, energy for UV disinfection, and the potential for formation of disinfection byproducts. Copyright © 2017 Elsevier Ltd. All rights reserved.

Water quality data for national-scale aquatic research: The Water Quality Portal

Science.gov (United States)

Read, Emily K.; Carr, Lindsay; DeCicco, Laura; Dugan, Hilary; Hanson, Paul C.; Hart, Julia A.; Kreft, James; Read, Jordan S.; Winslow, Luke

2017-01-01

Aquatic systems are critical to food, security, and society. But, water data are collected by hundreds of research groups and organizations, many of which use nonstandard or inconsistent data descriptions and dissemination, and disparities across different types of water observation systems represent a major challenge for freshwater research. To address this issue, the Water Quality Portal (WQP) was developed by the U.S. Environmental Protection Agency, the U.S. Geological Survey, and the National Water Quality Monitoring Council to be a single point of access for water quality data dating back more than a century. The WQP is the largest standardized water quality data set available at the time of this writing, with more than 290 million records from more than 2.7 million sites in groundwater, inland, and coastal waters. The number of data contributors, data consumers, and third-party application developers making use of the WQP is growing rapidly. Here we introduce the WQP, including an overview of data, the standardized data model, and data access and services; and we describe challenges and opportunities associated with using WQP data. We also demonstrate through an example the value of the WQP data by characterizing seasonal variation in lake water clarity for regions of the continental U.S. The code used to access, download, analyze, and display these WQP data as shown in the figures is included as supporting information.

Geospatial distribution modeling and determining suitability of groundwater quality for irrigation purpose using geospatial methods and water quality index (WQI) in Northern Ethiopia

Science.gov (United States)

Gidey, Amanuel

2018-06-01

Determining suitability and vulnerability of groundwater quality for irrigation use is a key alarm and first aid for careful management of groundwater resources to diminish the impacts on irrigation. This study was conducted to determine the overall suitability of groundwater quality for irrigation use and to generate their spatial distribution maps in Elala catchment, Northern Ethiopia. Thirty-nine groundwater samples were collected to analyze and map the water quality variables. Atomic absorption spectrophotometer, ultraviolet spectrophotometer, titration and calculation methods were used for laboratory groundwater quality analysis. Arc GIS, geospatial analysis tools, semivariogram model types and interpolation methods were used to generate geospatial distribution maps. Twelve and eight water quality variables were used to produce weighted overlay and irrigation water quality index models, respectively. Root-mean-square error, mean square error, absolute square error, mean error, root-mean-square standardized error, measured values versus predicted values were used for cross-validation. The overall weighted overlay model result showed that 146 km2 areas are highly suitable, 135 km2 moderately suitable and 60 km2 area unsuitable for irrigation use. The result of irrigation water quality index confirms 10.26% with no restriction, 23.08% with low restriction, 20.51% with moderate restriction, 15.38% with high restriction and 30.76% with the severe restriction for irrigation use. GIS and irrigation water quality index are better methods for irrigation water resources management to achieve a full yield irrigation production to improve food security and to sustain it for a long period, to avoid the possibility of increasing environmental problems for the future generation.

ECONOMETRIC MODELLING OD THE INFLUENCE OF LAKE WATER QUALITY CHANGES ON FISHING ECONOMY

Directory of Open Access Journals (Sweden)

Marek Antoni Ramczyk

2017-06-01

Full Text Available The econometric model can be a precise instrument for the analysis of the impact of the natural environment's degradation on fishing economy. This paper aims at analysing the influence of the water quality changes in lake Charzykowskie on the fishing economy. This dissertation present the results of a research on the lake water pollution's impact on fishing economy. The economic-ecological models have been constructed, explaining the changes of economic effects of the lake fishery in the conditions of an increasing water pollution in the epilimnion on the example of the catch of Rutilus rutilus, Abramis brama, Blicca bjoerkna, Coregonus albula, Coregonus lavaretus, Anguilla anguilla and Esox lucius in Lake Charzykowskie. Performed empirical research looked into the influence of the environmental factors on the size of fish catch. Calculations and analysis show clearly that though the habitat factors do influence the catch size of each studied fish species, they do it with different intensity and in various combinations. Both lake water quality and climate factors changes cause measurable effects on fishing industry of lake Charzykowskie. Among all the examined Rutilus rutilus, Abramis brama and Blicca bjoerkna the highest environmental requirements concerning water quality has Blicca bjoerkna. Whereas Abramis brama has slightly higher environmental requirements than Rutilus rutilus. Empirical calculations showed as well that Coregonus albula and Coregonus lavaretus have considerably higher water cleanness requirements than Rutilus rutilus, Abramis brama and Blicca bjoerkna. While when talking about Rutilus rutilus, Abramis brama and Blicca bjoerkna, most water characteristics still rather stimulated these species' development, when it comes to Coregonus albula and Coregonus lavaretus, in general they suppressed their development. The model has also proved quite high habitat requierements of Anquilla anquilla and correctness of the thesis that

Water-Quality Data

Science.gov (United States)

... Water Quality? [1.7MB PDF] Past featured science... Water Quality Data Today's Water Conditions Get continuous real- ... list of USGS water-quality data resources . USGS Water Science Areas Water Resources Groundwater Surface Water Water ...

Evaluating Water Supply and Water Quality Management Options for Las Vegas Valley

Science.gov (United States)

Ahmad, S.

2007-05-01

The ever increasing population in Las Vegas is generating huge demand for water supply on one hand and need for infrastructure to collect and treat the wastewater on the other hand. Current plans to address water demand include importing water from Muddy and Virgin Rivers and northern counties, desalination of seawater with trade- payoff in California, water banking in Arizona and California, and more intense water conservation efforts in the Las Vegas Valley (LVV). Water and wastewater in the LVV are intrinsically related because treated wastewater effluent is returned back to Lake Mead, the drinking water source for the Valley, to get a return credit thereby augmenting Nevada's water allocation from the Colorado River. The return of treated wastewater however, is a major contributor of nutrients and other yet unregulated pollutants to Lake Mead. Parameters that influence the quantity of water include growth of permanent and transient population (i.e., tourists), indoor and outdoor water use, wastewater generation, wastewater reuse, water conservation, and return flow credits. The water quality of Lake Mead and the Colorado River is affected by the level of treatment of wastewater, urban runoff, groundwater seepage, and a few industrial inputs. We developed an integrated simulation model, using system dynamics modeling approach, to account for both water quantity and quality in the LVV. The model captures the interrelationships among many variables that influence both, water quantity and water quality. The model provides a valuable tool for understanding past, present and future pathways of water and its constituents in the LVV. The model is calibrated and validated using the available data on water quantity (flows at water and wastewater treatment facilities and return water credit flow rates) and water quality parameters (TDS and phosphorus concentrations). We used the model to explore important questions: a)What would be the effect of the water transported from

Optimizing basin-scale coupled water quantity and water quality management with stochastic dynamic programming

DEFF Research Database (Denmark)

Davidsen, Claus; Liu, Suxia; Mo, Xingguo

2015-01-01

Few studies address water quality in hydro-economic models, which often focus primarily on optimal allocation of water quantities. Water quality and water quantity are closely coupled, and optimal management with focus solely on either quantity or quality may cause large costs in terms of the oth......-er component. In this study, we couple water quality and water quantity in a joint hydro-economic catchment-scale optimization problem. Stochastic dynamic programming (SDP) is used to minimize the basin-wide total costs arising from water allocation, water curtailment and water treatment. The simple water...... quality module can handle conservative pollutants, first order depletion and non-linear reactions. For demonstration purposes, we model pollutant releases as biochemical oxygen demand (BOD) and use the Streeter-Phelps equation for oxygen deficit to compute the resulting min-imum dissolved oxygen...

Water quality

Science.gov (United States)

Aquatic animals are healthiest and grow best when environmental conditions are within certain ranges that define, for a particular species, “good” water quality. From the outset, successful aquaculture requires a high-quality water supply. Water quality in aquaculture systems also deteriorates as an...

Integrated Urban Water Quality Management

DEFF Research Database (Denmark)

Rauch, W.; Harremoës, Poul

1995-01-01

The basic features of integrated urban water quality management by means of deterministic modeling are outlined. Procedures for the assessment of the detrimental effects in the recipient are presented as well as the basic concepts of an integrated model. The analysis of a synthetic urban drainage...... system provides useful information for water quality management. It is possible to identify the system parameters that contain engineering significance. Continuous simulation of the system performance indicates that the combined nitrogen loading is dominated by the wastewater treatment plant during dry...

Hydrodynamic modelling of recreational water quality using Escherichia coli as an indicator of microbial contamination

Science.gov (United States)

Eregno, Fasil Ejigu; Tryland, Ingun; Tjomsland, Torulv; Kempa, Magdalena; Heistad, Arve

2018-06-01

Microbial contamination of recreational beaches is often at its worst after heavy rainfall events due to storm floods that carry fecal matter and other pollutants from the watershed. Similarly, overflows of untreated sewage from combined sewerage systems may discharge directly into coastal water or via rivers and streams. In order to understand the effect of rainfall events, wind-directions and tides on the recreational water quality, GEMSS, an integrated 3D hydrodynamic model was applied to assess the spreading of Escherichia coli (E. coli) at the Sandvika beaches, located in the Oslo fjord. The model was also used to theoretically investigate the effect of discharges from septic tanks from boats on the water quality at local beaches. The model make use of microbial decay rate as the main input representing the survival of microbial pathogens in the ocean, which vary widely depending on the type of pathogen and environmental stress. The predicted beach water quality was validated against observed data after a heavy rainfall event using Nash-Sutcliffe coefficient (E) and the overall result indicated that the model performed quite well and the simulation was in - good agreement with the observed E. coli concentrations for all beaches. The result of this study indicated that: 1) the bathing water quality was poor according to the EU bathing water directive up to two days after the heavy rainfall event depending on the location of the beach site. 2) The discharge from a boat at 300-meter distance to the beaches slightly increased the E. coli levels at the beaches. 3) The spreading of microbial pathogens from its source to the different beaches depended on the wind speed and the wind direction.

Water quality data for national-scale aquatic research: The Water Quality Portal

Science.gov (United States)

Read, Emily K.; Carr, Lindsay; De Cicco, Laura; Dugan, Hilary A.; Hanson, Paul C.; Hart, Julia A.; Kreft, James; Read, Jordan S.; Winslow, Luke A.

2017-02-01

xml:id="wrcr22485-sec-1001" numbered="no">Aquatic systems are critical to food, security, and society. But, water data are collected by hundreds of research groups and organizations, many of which use nonstandard or inconsistent data descriptions and dissemination, and disparities across different types of water observation systems represent a major challenge for freshwater research. To address this issue, the Water Quality Portal (WQP) was developed by the U.S. Environmental Protection Agency, the U.S. Geological Survey, and the National Water Quality Monitoring Council to be a single point of access for water quality data dating back more than a century. The WQP is the largest standardized water quality data set available at the time of this writing, with more than 290 million records from more than 2.7 million sites in groundwater, inland, and coastal waters. The number of data contributors, data consumers, and third-party application developers making use of the WQP is growing rapidly. Here we introduce the WQP, including an overview of data, the standardized data model, and data access and services; and we describe challenges and opportunities associated with using WQP data. We also demonstrate through an example the value of the WQP data by characterizing seasonal variation in lake water clarity for regions of the continental U.S. The code used to access, download, analyze, and display these WQP data as shown in the figures is included as supporting information.

Modeling Water Clarity and Light Quality in Oceans

Science.gov (United States)

Phytoplankton is a primary producer of organic compounds, and it forms the base of the food chain in ocean waters. The concentration of phytoplankton in the water column controls water clarity and the amount and quality of light that penetrates through it. The availability of ade...

Quantifying effects of hydrological and water quality disturbances on fish with food-web modeling

Science.gov (United States)

Zhao, Changsen; Zhang, Yuan; Yang, Shengtian; Xiang, Hua; Sun, Ying; Yang, Zengyuan; Yu, Qiang; Lim, Richard P.

2018-05-01

Accurately delineating the effects of hydrological and water quality habitat factors on the aquatic biota will significantly assist the management of water resources and restoration of river ecosystems. However, current models fail to comprehensively consider the effects of multiple habitat factors on the development of fish species. In this study, a dynamic framework for river ecosystems was set up to explore the effects of multiple habitat factors in terms of hydrology and water quality on the fish community in rivers. To achieve this the biomechanical forms of the relationships between hydrology, water quality, and aquatic organisms were determined. The developing processes of the food web without external disturbance were simulated by 208 models, constructed using Ecopath With Ecosim (EWE). These models were then used to analyze changes in biomass (ΔB) of two representative fish species, Opsariichthys bidens and Carassius auratus, which are widely distributed in Asia, and thus have attracted the attention of scholars and stakeholders, due to the consequence of habitat alteration. Results showed that the relationship between the changes in fish biomass and key habitat factors can be expressed in a unified form. T-tests for the unified form revealed that the means of the two data sets of simulated and observed ΔB for these two fish species (O. bidens and C. auratus) were equal at the significance level of 5%. Compared with other ecological dynamic models, our framework includes theories that are easy to understand and has modest requirements for assembly and scientific expertise. Moreover, this framework can objectively assess the influence of hydrological and water quality variance on aquatic biota with simpler theory and little expertise. Therefore, it is easy to be put into practice and can provide a scientific support for decisions in ecological restoration made by river administrators and stakeholders across the world.

Real-time water quality monitoring and providing water quality ...

Science.gov (United States)

EPA and the U.S. Geological Survey (USGS) have initiated the “Village Blue” research project to provide real-time water quality monitoring data to the Baltimore community and increase public awareness about local water quality in Baltimore Harbor and the Chesapeake Bay. The Village Blue demonstration project complements work that a number of state and local organizations are doing to make Baltimore Harbor “swimmable and fishable” 2 by 2020. Village Blue is designed to build upon EPA’s “Village Green” project which provides real-time air quality information to communities in six locations across the country. The presentation, “Real-time water quality monitoring and providing water quality information to the Baltimore Community”, summarizes the Village Blue real-time water quality monitoring project being developed for the Baltimore Harbor.

Conjunctively optimizing flash flood control and water quality in urban water reservoirs by model predictive control and dynamic emulation

Science.gov (United States)

Galelli, Stefano; Goedbloed, Albert; Schmitter, Petra; Castelletti, Andrea

2014-05-01

Urban water reservoirs are a viable adaptation option to account for increasing drinking water demand of urbanized areas as they allow storage and re-use of water that is normally lost. In addition, the direct availability of freshwater reduces pumping costs and diversifies the portfolios of drinking water supply. Yet, these benefits have an associated twofold cost. Firstly, the presence of large, impervious areas increases the hydraulic efficiency of urban catchments, with short time of concentration, increased runoff rates, losses of infiltration and baseflow, and higher risk of flash floods. Secondly, the high concentration of nutrients and sediments characterizing urban discharges is likely to cause water quality problems. In this study we propose a new control scheme combining Model Predictive Control (MPC), hydro-meteorological forecasts and dynamic model emulation to design real-time operating policies that conjunctively optimize water quantity and quality targets. The main advantage of this scheme stands in its capability of exploiting real-time hydro-meteorological forecasts, which are crucial in such fast-varying systems. In addition, the reduced computational requests of the MPC scheme allows coupling it with dynamic emulators of water quality processes. The approach is demonstrated on Marina Reservoir, a multi-purpose reservoir located in the heart of Singapore and characterized by a large, highly urbanized catchment with a short (i.e. approximately one hour) time of concentration. Results show that the MPC scheme, coupled with a water quality emulator, provides a good compromise between different operating objectives, namely flood risk reduction, drinking water supply and salinity control. Finally, the scheme is used to assess the effect of source control measures (e.g. green roofs) aimed at restoring the natural hydrological regime of Marina Reservoir catchment.

Water quality relationships and evaluation using a new water quality index

International Nuclear Information System (INIS)

Said, A.; Stevens, D.; Sehlke, G.

2002-01-01

Water quality is dependent on a variety of measures, including dissolved oxygen, microbial contamination, turbidity, nutrients, temperature, pH, and other constituents. Determining relationships between water quality parameters can improve water quality assessment, and watershed management. In addition, these relationships can be very valuable in case of evaluating water quality in watersheds that have few water quality data. (author)

Water quality modeling based on landscape analysis: Importance of riparian hydrology

Science.gov (United States)

Thomas Grabs

2010-01-01

Several studies in high-latitude catchments have demonstrated the importance of near-stream riparian zones as hydrogeochemical hotspots with a substantial influence on stream chemistry. An adequate representation of the spatial variability of riparian-zone processes and characteristics is the key for modeling spatiotemporal variations of stream-water quality. This...

A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model

Science.gov (United States)

Abbaspour, K. C.; Rouholahnejad, E.; Vaghefi, S.; Srinivasan, R.; Yang, H.; Kløve, B.

2015-05-01

A combination of driving forces are increasing pressure on local, national, and regional water supplies needed for irrigation, energy production, industrial uses, domestic purposes, and the environment. In many parts of Europe groundwater quantity, and in particular quality, have come under sever degradation and water levels have decreased resulting in negative environmental impacts. Rapid improvements in the economy of the eastern European block of countries and uncertainties with regard to freshwater availability create challenges for water managers. At the same time, climate change adds a new level of uncertainty with regard to freshwater supplies. In this research we build and calibrate an integrated hydrological model of Europe using the Soil and Water Assessment Tool (SWAT) program. Different components of water resources are simulated and crop yield and water quality are considered at the Hydrological Response Unit (HRU) level. The water resources are quantified at subbasin level with monthly time intervals. Leaching of nitrate into groundwater is also simulated at a finer spatial level (HRU). The use of large-scale, high-resolution water resources models enables consistent and comprehensive examination of integrated system behavior through physically-based, data-driven simulation. In this article we discuss issues with data availability, calibration of large-scale distributed models, and outline procedures for model calibration and uncertainty analysis. The calibrated model and results provide information support to the European Water Framework Directive and lay the basis for further assessment of the impact of climate change on water availability and quality. The approach and methods developed are general and can be applied to any large region around the world.

Inland-coastal water interaction: Remote sensing application for shallow-water quality and algal blooms modeling

Science.gov (United States)

Melesse, Assefa; Hajigholizadeh, Mohammad; Blakey, Tara

2017-04-01

In this study, Landsat 8 and Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) sensors were used to model the spatiotemporal changes of four water quality parameters: Landsat 8 (turbidity, chlorophyll-a (chl-a), total phosphate, and total nitrogen) and Sea-Viewing Wide Field-of-View Sensor (SeaWIFS) (algal blooms). The study was conducted in Florda bay, south Florida and model outputs were compared with in-situ observed data. The Landsat 8 based study found that, the predictive models to estimate chl-a and turbidity concentrations, developed through the use of stepwise multiple linear regression (MLR), gave high coefficients of determination in dry season (wet season) (R2 = 0.86(0.66) for chl-a and R2 = 0.84(0.63) for turbidity). Total phosphate and TN were estimated using best-fit multiple linear regression models as a function of Landsat TM and OLI,127 and ground data and showed a high coefficient of determination in dry season (wet season) (R2 = 0.74(0.69) for total phosphate and R2 = 0.82(0.82) for TN). Similarly, the ability of SeaWIFS for chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels' benthic class was evaluated. Benthic class was determined through satellite image-based classification methods. It was found that benthic class based chl-a modeling algorithm was better than the existing regionally-tuned approach. Evaluation of the residuals indicated the potential for further improvement to chl-a estimation through finer characterization of benthic environments. Key words: Landsat, SeaWIFS, water quality, Florida bay, Chl-a, turbidity

The role of pesticide fate modelling in a prevention-led approach to potable water quality management

Science.gov (United States)

Dolan, Tom; Pullan, Stephanie; Whelan, Mick; Parsons, David

2013-04-01

Diffuse inputs from agriculture are commonly the main source of pesticide contamination in surface water and may have implications for the quality of treated drinking water. After privatisation in 1991, UK water companies primarily focused on the provision of sufficient water treatment to reduce the risk of non-compliance with the European Drinking Water Directive (DWD), under which all pesticide concentrations must be below 0.1µg/l and UK Water Supply Regulations for the potable water they supply. Since 2000, Article 7 of the Water Framework Directive (WFD) has begun to drive a prevention-led approach to compliance with the DWD. As a consequence water companies are now more interested in the quality of 'raw' (untreated) water at the point of abstraction. Modelling (based upon best available estimates of cropping, pesticide use, weather conditions, pesticide characteristics, and catchment characteristics) and monitoring of raw water quality can both help to determine the compliance risks associated with the quality of this 'raw' water resource. This knowledge allows water companies to prioritise active substances for action in their catchments, and is currently used in many cases to support the design of monitoring programmes for pesticide active substances. Additional value can be provided if models are able to help to identify the type and scale of catchment management interventions required to achieve DWD compliance for pesticide active substances through pollution prevention at source or along transport pathways. These questions were explored using a simple catchment-scale pesticide fate and transport model. The model employs a daily time-step and is semi-lumped with calculations performed for soil type and crop combinations, weighted by their proportions within the catchment. Soil properties are derived from the national soil database and the model can, therefore, be applied to any catchment in England and Wales. Various realistic catchment management

Identification and assessment of potential water quality impact factors for drinking-water reservoirs.

Science.gov (United States)

Gu, Qing; Deng, Jinsong; Wang, Ke; Lin, Yi; Li, Jun; Gan, Muye; Ma, Ligang; Hong, Yang

2014-06-10

Various reservoirs have been serving as the most important drinking water sources in Zhejiang Province, China, due to the uneven distribution of precipitation and severe river pollution. Unfortunately, rapid urbanization and industrialization have been continuously challenging the water quality of the drinking-water reservoirs. The identification and assessment of potential impacts is indispensable in water resource management and protection. This study investigates the drinking water reservoirs in Zhejiang Province to better understand the potential impact on water quality. Altogether seventy-three typical drinking reservoirs in Zhejiang Province encompassing various water storage levels were selected and evaluated. Using fifty-two reservoirs as training samples, the classification and regression tree (CART) method and sixteen comprehensive variables, including six sub-sets (land use, population, socio-economy, geographical features, inherent characteristics, and climate), were adopted to establish a decision-making model for identifying and assessing their potential impacts on drinking-water quality. The water quality class of the remaining twenty-one reservoirs was then predicted and tested based on the decision-making model, resulting in a water quality class attribution accuracy of 81.0%. Based on the decision rules and quantitative importance of the independent variables, industrial emissions was identified as the most important factor influencing the water quality of reservoirs; land use and human habitation also had a substantial impact on water quality. The results of this study provide insights into the factors impacting the water quality of reservoirs as well as basic information for protecting reservoir water resources.

Development Smart Water Aquaponics Model

Directory of Open Access Journals (Sweden)

Gheorghe Adrian ZUGRAVU

2017-06-01

Full Text Available The present paper contributes to the modeling aquaculture. The paper main objectives are to identify an analysis smart water aquaponics. The purpose is to add more value to end aquaponics products. Aquaculture production depends on physical, chemical and biological qualities of pond water to a greater extent. The successful pond management requires an understanding of water quality. Intensification of pond makes the water quality undesirable with a number of water quality parameters. The objective of this model is to test and predicts plant and fish growth and net ammonium and nitrate concentrations in water in an aquaponic system. This is done by comparing the model outputs with measurements under controlled conditions in order to assess the accuracy of the tool to simulate nutrient concentrations in water and fish and plant biomass production of the system.

Water quality index for assessment of water quality of river ravi at ...

African Journals Online (AJOL)

Water quality of River Ravi, a tributary of Indus River System was evaluated by Water Quality Index (WQI) technique. A water quality index provides a single number that expresses overall water quality at a certain location and time based on several water quality parameters. The objective of an index is to turn complex water ...

Multi-objective optimization of water quality, pumps operation, and storage sizing of water distribution systems.

Science.gov (United States)

Kurek, Wojciech; Ostfeld, Avi

2013-01-30

A multi-objective methodology utilizing the Strength Pareto Evolutionary Algorithm (SPEA2) linked to EPANET for trading-off pumping costs, water quality, and tanks sizing of water distribution systems is developed and demonstrated. The model integrates variable speed pumps for modeling the pumps operation, two water quality objectives (one based on chlorine disinfectant concentrations and one on water age), and tanks sizing cost which are assumed to vary with location and diameter. The water distribution system is subject to extended period simulations, variable energy tariffs, Kirchhoff's laws 1 and 2 for continuity of flow and pressure, tanks water level closure constraints, and storage-reliability requirements. EPANET Example 3 is employed for demonstrating the methodology on two multi-objective models, which differ in the imposed water quality objective (i.e., either with disinfectant or water age considerations). Three-fold Pareto optimal fronts are presented. Sensitivity analysis on the storage-reliability constraint, its influence on pumping cost, water quality, and tank sizing are explored. The contribution of this study is in tailoring design (tank sizing), pumps operational costs, water quality of two types, and reliability through residual storage requirements, in a single multi-objective framework. The model was found to be stable in generating multi-objective three-fold Pareto fronts, while producing explainable engineering outcomes. The model can be used as a decision tool for both pumps operation, water quality, required storage for reliability considerations, and tank sizing decision-making. Copyright © 2012 Elsevier Ltd. All rights reserved.

Water quality modeling in the dead end sections of drinking water (Supplement)

Data.gov (United States)

U.S. Environmental Protection Agency — Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to...

Primer on Water Quality

Science.gov (United States)

... water quality. What do we mean by "water quality"? Water quality can be thought of as a measure ... is suitable for a particular use. How is water quality measured? Some aspects of water quality can be ...

Practical Application of Sea Water Quality Mathematical Model for the Black Sea Coast of Sochi

Directory of Open Access Journals (Sweden)

Oleg A. Burunin

2013-01-01

Full Text Available The article deals with an application of the developed model of the sea water quality for forecasting of coastal waters indicators change in the artificial coastal water areas of Sochi. Results of the researches conducted in relation to yacht port «Grand Marina Sochi» are considered.

Modelling the impact of future socio-economic and climate change scenarios on river microbial water quality.

Science.gov (United States)

Islam, M M Majedul; Iqbal, Muhammad Shahid; Leemans, Rik; Hofstra, Nynke

2018-03-01

Microbial surface water quality is important, as it is related to health risk when the population is exposed through drinking, recreation or consumption of irrigated vegetables. The microbial surface water quality is expected to change with socio-economic development and climate change. This study explores the combined impacts of future socio-economic and climate change scenarios on microbial water quality using a coupled hydrodynamic and water quality model (MIKE21FM-ECOLab). The model was applied to simulate the baseline (2014-2015) and future (2040s and 2090s) faecal indicator bacteria (FIB: E. coli and enterococci) concentrations in the Betna river in Bangladesh. The scenarios comprise changes in socio-economic variables (e.g. population, urbanization, land use, sanitation and sewage treatment) and climate variables (temperature, precipitation and sea-level rise). Scenarios have been developed building on the most recent Shared Socio-economic Pathways: SSP1 and SSP3 and Representative Concentration Pathways: RCP4.5 and RCP8.5 in a matrix. An uncontrolled future results in a deterioration of the microbial water quality (+75% by the 2090s) due to socio-economic changes, such as higher population growth, and changes in rainfall patterns. However, microbial water quality improves under a sustainable scenario with improved sewage treatment (-98% by the 2090s). Contaminant loads were more influenced by changes in socio-economic factors than by climatic change. To our knowledge, this is the first study that combines climate change and socio-economic development scenarios to simulate the future microbial water quality of a river. This approach can also be used to assess future consequences for health risks. Copyright © 2017 The Authors. Published by Elsevier GmbH.. All rights reserved.

Applications of MIDAS regression in analysing trends in water quality

Science.gov (United States)

Penev, Spiridon; Leonte, Daniela; Lazarov, Zdravetz; Mann, Rob A.

2014-04-01

We discuss novel statistical methods in analysing trends in water quality. Such analysis uses complex data sets of different classes of variables, including water quality, hydrological and meteorological. We analyse the effect of rainfall and flow on trends in water quality utilising a flexible model called Mixed Data Sampling (MIDAS). This model arises because of the mixed frequency in the data collection. Typically, water quality variables are sampled fortnightly, whereas the rain data is sampled daily. The advantage of using MIDAS regression is in the flexible and parsimonious modelling of the influence of the rain and flow on trends in water quality variables. We discuss the model and its implementation on a data set from the Shoalhaven Supply System and Catchments in the state of New South Wales, Australia. Information criteria indicate that MIDAS modelling improves upon simplistic approaches that do not utilise the mixed data sampling nature of the data.

Modeling water quality in the middle segment of the Luyano River

International Nuclear Information System (INIS)

Valcarcel Rojas, Lino; Alberro Macias, Nancy; Rodriguez GonzalesZahilys; Herrero, Maydel; Borroto Portela, Jorge; Rodrigues Garcez, Anel; Dominguez Catases, Judith; Griffith Martinez, Jose; Derivet Zarzabal, Milagros; Flores Juan, Pedro; Cuesta Borges, Jaime

2010-01-01

The methodology for the modelling of three parameters that characterize the quality of water: Biochemical Oxygen Demand, Dissolved Oxygen and ammonium in a stretch of Luyano river using the software RIOSep v.2.0. The procedure combined the use of radiotracer techniques for estimating the hydrodynamic parameters of the current with physicochemical techniques for the determination of its basic parameters. The lifting of the hydrodynamic parameters in the current was conducted with the use of 99mTc as a radiotracer. Simultaneously with flow determination, water was sampled at five stations in the main channel and two tributaries, in order to determine the physicochemical parameters of interest. The result was a model that describes accurately the Biochemical Oxygen Demand and Dissolved Oxygen behaviour (more than 90%), and showed good result for ammonium, so it adequately characterizes the processes of purification and oxygen balance in the water. (Author)

Applying a water quality index model to assess the water quality of the major rivers in the Kathmandu Valley, Nepal.

Science.gov (United States)

Regmi, Ram Krishna; Mishra, Binaya Kumar; Masago, Yoshifumi; Luo, Pingping; Toyozumi-Kojima, Asako; Jalilov, Shokhrukh-Mirzo

2017-08-01

Human activities during recent decades have led to increased degradation of the river water environment in South Asia. This degradation has led to concerns for the populations of the major cities of Nepal, including those of the Kathmandu Valley. The deterioration of the rivers in the valley is directly linked to the prevalence of poor sanitary conditions, as well as the presence of industries that discharge their effluents into the river. This study aims to investigate the water quality aspect for the aquatic ecosystems and recreation of the major rivers in the Kathmandu Valley using the Canadian Council of Ministers of the Environment water quality index (CCME WQI). Ten physicochemical parameters were used to determine the CCME WQI at 20 different sampling locations. Analysis of the data indicated that the water quality in rural areas ranges from excellent to good, whereas in denser settlements and core urban areas, the water quality is poor. The study results are expected to provide policy-makers with valuable information related to the use of river water by local people in the study area.

Assessment of Dissolved Oxygen Mitigation at Hydropower Dams Using an Integrated Hydrodynamic/Water Quality/Fish Growth Model

Energy Technology Data Exchange (ETDEWEB)

Bevelhimer, Mark S [ORNL; Coutant, Charles C [ORNL

2006-07-01

Dissolved oxygen (DO) in rivers is a common environmental problem associated with hydropower projects. Approximately 40% of all FERC-licensed projects have requirements to monitor and/or mitigate downstream DO conditions. Most forms of mitigation for increasing DO in dam tailwaters are fairly expensive. One area of research of the Department of Energy's Hydropower Program is the development of advanced turbines that improve downstream water quality and have other environmental benefits. There is great interest in being able to predict the benefits of these modifications prior to committing to the cost of new equipment. In the case of turbine replacement or modification, there is a need for methods that allow us to accurately extrapolate the benefits derived from one or two turbines with better design to the replacement or modification of all turbines at a site. The main objective of our study was to demonstrate a modeling approach that integrates the effects of flow and water quality dynamics with fish bioenergetics to predict DO mitigation effectiveness over long river segments downstream of hydropower dams. We were particularly interested in demonstrating the incremental value of including a fish growth model as a measure of biological response. The models applied are a suite of tools (RMS4 modeling system) originally developed by the Tennessee Valley Authority for simulating hydrodynamics (ADYN model), water quality (RQUAL model), and fish growth (FISH model) as influenced by DO, temperature, and available food base. We parameterized a model for a 26-mile reach of the Caney Fork River (Tennessee) below Center Hill Dam to assess how improvements in DO at the dam discharge would affect water quality and fish growth throughout the river. We simulated different types of mitigation (i.e., at the turbine and in the reservoir forebay) and different levels of improvement. The model application successfully demonstrates how a modeling approach like this one can be

Development of urban runoff model FFC-QUAL for first-flush water-quality analysis in urban drainage basins.

Science.gov (United States)

Hur, Sungchul; Nam, Kisung; Kim, Jungsoo; Kwak, Changjae

2018-01-01

An urban runoff model that is able to compute the runoff, the pollutant loadings, and the concentrations of water-quality constituents in urban drainages during the first flush was developed. This model, which is referred to as FFC-QUAL, was modified from the existing ILLUDAS model and added for use during the water-quality analysis process for dry and rainy periods. For the dry period, the specifications of the coefficients for the discharge and water quality were used. During rainfall, we used the Clark and time-area methods for the runoff analyses of pervious and impervious areas to consider the effects of the subbasin shape; moreover, four pollutant accumulation methods and the washoff equation for computing the water quality each time were used. According to the verification results, FFC-QUAL provides generally similar output as the measured data for the peak flow, total runoff volume, total loadings, peak concentration, and time of peak concentration for three rainfall events in the Gunja subbasin. In comparison with the ILLUDAS, SWMM, and MOUSE models, there is little difference between these models and the model developed in this study. The proposed model should be useful in urban watersheds because of its simplicity and its capacity to model common pollutants (e.g., biological oxygen demand, chemical oxygen demand, Escherichia coli, suspended solids, and total nitrogen and phosphorous) in runoff. The proposed model can also be used in design studies to determine how changes in infrastructure will affect the runoff and pollution loads. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

A water quality index model using stepwise regression and neural networks models for the Piabanha River basin in Rio de Janeiro, Brazil

Science.gov (United States)

Villas Boas, M. D.; Olivera, F.; Azevedo, J. S.

2013-12-01

The evaluation of water quality through 'indexes' is widely used in environmental sciences. There are a number of methods available for calculating water quality indexes (WQI), usually based on site-specific parameters. In Brazil, WQI were initially used in the 1970s and were adapted from the methodology developed in association with the National Science Foundation (Brown et al, 1970). Specifically, the WQI 'IQA/SCQA', developed by the Institute of Water Management of Minas Gerais (IGAM), is estimated based on nine parameters: Temperature Range, Biochemical Oxygen Demand, Fecal Coliforms, Nitrate, Phosphate, Turbidity, Dissolved Oxygen, pH and Electrical Conductivity. The goal of this study was to develop a model for calculating the IQA/SCQA, for the Piabanha River basin in the State of Rio de Janeiro (Brazil), using only the parameters measurable by a Multiparameter Water Quality Sonde (MWQS) available in the study area. These parameters are: Dissolved Oxygen, pH and Electrical Conductivity. The use of this model will allow to further the water quality monitoring network in the basin, without requiring significant increases of resources. The water quality measurement with MWQS is less expensive than the laboratory analysis required for the other parameters. The water quality data used in the study were obtained by the Geological Survey of Brazil in partnership with other public institutions (i.e. universities and environmental institutes) as part of the project "Integrated Studies in Experimental and Representative Watersheds". Two models were developed to correlate the values of the three measured parameters and the IQA/SCQA values calculated based on all nine parameters. The results were evaluated according to the following validation statistics: coefficient of determination (R2), Root Mean Square Error (RMSE), Akaike information criterion (AIC) and Final Prediction Error (FPE). The first model was a linear stepwise regression between three independent variables

Modelling receiving water quality responses to brackishwater shrimp aquaculture farm effluents

International Nuclear Information System (INIS)

Roy Chaudhury, R.K.; Ramana Murty, V.; Ravindran, M.

1999-01-01

The objective was to perform a waste load allocation and determine the extent of aquaculture that the creeks can sustain, by meeting the water quality criteria for both the creek ecosystem and pond culture. Based on these results, similar assessments may be performed for other sites supporting large scale aquaculture activities. This paper introduces the sampling program and modelling methodology of the study

The role of hydrological and water quality models in the application of the ecosystem services framework for the EU Water Framework Directive

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Hallouin, Thibault; Bruen, Michael; Feeley, Hugh B.; Christie, Michael; Bullock, Craig; Kelly, Fiona; Kelly-Quinn, Mary

2017-04-01

The hydrological cycle is intimately linked with environmental processes that are essential for human welfare in many regards including, among others, the provision of safe water from surface and subsurface waterbodies, rain-fed agricultural production, or the provision of aquatic-sourced food. As well as being a receiver of these natural benefits, the human population is also a manager of the water and other natural resources and, as such, can affect their future sustainable provision. With global population growth and climate change, both the dependence of the human population on water resources and the threat they pose to these resources are likely to intensify so that the sustainability of the coupled natural and human system is threatened. In the European Union, the Water Framework Directive is driving policy and encouraging member states to manage their water resources wisely in order to maintain or restore ecological quality. To this end, the ecosystem services framework can be a useful tool to link the requirements in terms of ecological status into more tangible descriptors, that is the ecosystem services. In the ESManage Project, existing environmental system models such as hydrological models and water quality models are used as the basis to quantify the provision of many hydrological and aquatic ecosystem services by constructing indicators for the ecosystem services from the modelled environmental variables. By allowing different management options and policies to be compared, these models can be a valuable source of information for policy makers when they are used for climate and land use scenario analyses. Not all hydrological models developed for flood forecasting are suitable for this application and inappropriate models can lead to questionable conclusions. This paper demonstrates the readily available capabilities of a specially developed catchment hydrological model coupled with a water quality model to quantify a wide range of biophysically

Water quality and water rights in Colorado

International Nuclear Information System (INIS)

MacDonnell, L.J.

1989-07-01

The report begins with a review of early Colorado water quality law. The present state statutory system of water quality protection is summarized. Special attention is given to those provisions of Colorado's water quality law aimed at protecting water rights. The report then addresses several specific issues which involve the relationship between water quality and water use. Finally, recommendations are made for improving Colorado's approach to integrating quality and quantity concerns

Mitigation scenario analysis: modelling the impacts of changes in agricultural management practices on surface water quality at the catchment scale

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Taylor, Sam; He, Yi; Hiscock, Kevin

2014-05-01

Increasing human pressures on the natural environment through the demand for increased agricultural productivity have exacerbated and deteriorated water quality conditions within many environments due to an unbalancing of the nutrient cycle. As a consequence, increased agricultural diffuse water pollution has resulted in elevated concentrations of nutrients within surface water and groundwater bodies. This deterioration in water quality has direct consequences for the health of aquatic ecosystems and biodiversity, human health, and the use of water as a resource for public water supply and recreation. To mitigate these potential impacts and to meet commitments under the EU Drinking Water and Water Framework Directives, there is a need to improve our understanding of the impacts that agricultural land use and management practices have on water quality. Water quality models are one of the tools available which can be used to facilitate this aim. These simplified representations of the physical environment allow a variety of changes to be simulated within a catchment, including for example changes in agricultural land use and management practices, allowing for predictions of the impacts of those measures on water quality to be developed and an assessment to be made of their effectiveness in improving conditions. The aim of this research is to apply the water quality model SWAT (Soil and Water Assessment Tool) to the Wensum catchment (area 650 km2), situated in the East of England, to predict the impacts of potential changes in land use and land management practices on water quality as part of a process to select those measures that in combination will have the greatest potential to improve water quality. Model calibration and validation is conducted at three sites within the catchment against observations of river discharge and nitrate and total phosphorus loads at a monthly time-step using the optimisation algorithm SUFI-2 (Sequential Uncertainty Fitting Version 2

Developing and implementing the use of predictive models for estimating water quality at Great Lakes beaches

Science.gov (United States)

Francy, Donna S.; Brady, Amie M.G.; Carvin, Rebecca B.; Corsi, Steven R.; Fuller, Lori M.; Harrison, John H.; Hayhurst, Brett A.; Lant, Jeremiah; Nevers, Meredith B.; Terrio, Paul J.; Zimmerman, Tammy M.

2013-01-01

Predictive models have been used at beaches to improve the timeliness and accuracy of recreational water-quality assessments over the most common current approach to water-quality monitoring, which relies on culturing fecal-indicator bacteria such as Escherichia coli (E. coli.). Beach-specific predictive models use environmental and water-quality variables that are easily and quickly measured as surrogates to estimate concentrations of fecal-indicator bacteria or to provide the probability that a State recreational water-quality standard will be exceeded. When predictive models are used for beach closure or advisory decisions, they are referred to as “nowcasts.” During the recreational seasons of 2010-12, the U.S. Geological Survey (USGS), in cooperation with 23 local and State agencies, worked to improve existing nowcasts at 4 beaches, validate predictive models at another 38 beaches, and collect data for predictive-model development at 7 beaches throughout the Great Lakes. This report summarizes efforts to collect data and develop predictive models by multiple agencies and to compile existing information on the beaches and beach-monitoring programs into one comprehensive report. Local agencies measured E. coli concentrations and variables expected to affect E. coli concentrations such as wave height, turbidity, water temperature, and numbers of birds at the time of sampling. In addition to these field measurements, equipment was installed by the USGS or local agencies at or near several beaches to collect water-quality and metrological measurements in near real time, including nearshore buoys, weather stations, and tributary staff gages and monitors. The USGS worked with local agencies to retrieve data from existing sources either manually or by use of tools designed specifically to compile and process data for predictive-model development. Predictive models were developed by use of linear regression and (or) partial least squares techniques for 42 beaches

Extending a Consensus-based Fuzzy Ordered Weighting Average (FOWA Model in New Water Quality Indices

Directory of Open Access Journals (Sweden)

Mohammad Ali Baghapour

2017-07-01

Full Text Available In developing a specific WQI (Water Quality Index, many water quality parameters are involved with different levels of importance. The impact of experts’ different opinions and viewpoints, current risks affecting their opinions, and plurality of the involved parameters double the significance of the issue. Hence, the current study tries to apply a consensus-based FOWA (Fuzzy Ordered Weighting Average model as one of the most powerful and well-known Multi Criteria Decision Making (MCDM techniques to determine the importance of the used parameters in the development of such WQIs which is shown with an example. This operator has provided the capability of modeling the risks in decision-making through applying the optimistic degree of stakeholders and their power coupled with the use of fuzzy numbers. Totally, 22 water quality parameters for drinking purposes are considered in this study. To determine the weight of each parameter, the viewpoints of 4 decision-making groups of experts are taken into account. After determining the final weights, to validate the use of each parameter in a potential WQI, consensus degrees of both the decision makers and the parameters are calculated. All calculations are carried out by using the expertise software called Group Fuzzy Decision Making (GFDM. The highest and the lowest weight values, 0.999 and 0.073 respectively, are related to Hg and temperature. Regarding the type of consumption that is drinking, the parameters’ weights and ranks are consistent with their health impacts. Moreover, the decision makers’ highest and lowest consensus degrees were 0.9905 and 0.9669, respectively. Among the water quality parameters, temperature (with consensus degree of 0.9972 and Pb (with consensus degree of 0.9665, received the highest and lowest agreement from the decision making group. This study indicates that the weight of parameters in determining water quality largely depends on the experts’ opinions and

Section 3. The SPARROW Surface Water-Quality Model: Theory, Application and User Documentation

Science.gov (United States)

Schwarz, G.E.; Hoos, A.B.; Alexander, R.B.; Smith, R.A.

2006-01-01

SPARROW (SPAtially Referenced Regressions On Watershed attributes) is a watershed modeling technique for relating water-quality measurements made at a network of monitoring stations to attributes of the watersheds containing the stations. The core of the model consists of a nonlinear regression equation describing the non-conservative transport of contaminants from point and diffuse sources on land to rivers and through the stream and river network. The model predicts contaminant flux, concentration, and yield in streams and has been used to evaluate alternative hypotheses about the important contaminant sources and watershed properties that control transport over large spatial scales. This report provides documentation for the SPARROW modeling technique and computer software to guide users in constructing and applying basic SPARROW models. The documentation gives details of the SPARROW software, including the input data and installation requirements, and guidance in the specification, calibration, and application of basic SPARROW models, as well as descriptions of the model output and its interpretation. The documentation is intended for both researchers and water-resource managers with interest in using the results of existing models and developing and applying new SPARROW models. The documentation of the model is presented in two parts. Part 1 provides a theoretical and practical introduction to SPARROW modeling techniques, which includes a discussion of the objectives, conceptual attributes, and model infrastructure of SPARROW. Part 1 also includes background on the commonly used model specifications and the methods for estimating and evaluating parameters, evaluating model fit, and generating water-quality predictions and measures of uncertainty. Part 2 provides a user's guide to SPARROW, which includes a discussion of the software architecture and details of the model input requirements and output files, graphs, and maps. The text documentation and computer

A Prototype Educational Delivery System Using Water Quality Monitoring as a Model.

Science.gov (United States)

Glazer, Richard B.

This report describes the model educational delivery system used by Ulster County Community College in its water quality monitoring program. The educational delivery system described in the report encompasses the use of behavioral objectives as its foundation and builds upon this foundation to form a complete system whose outcomes can be measured,…

Effect of the spatiotemporal variability of rainfall inputs in water quality integrated catchment modelling for dissolved oxygen concentrations

Science.gov (United States)

Moreno Ródenas, Antonio Manuel; Cecinati, Francesca; ten Veldhuis, Marie-Claire; Langeveld, Jeroen; Clemens, Francois

2016-04-01

Maintaining water quality standards in highly urbanised hydrological catchments is a worldwide challenge. Water management authorities struggle to cope with changing climate and an increase in pollution pressures. Water quality modelling has been used as a decision support tool for investment and regulatory developments. This approach led to the development of integrated catchment models (ICM), which account for the link between the urban/rural hydrology and the in-river pollutant dynamics. In the modelled system, rainfall triggers the drainage systems of urban areas scattered along a river. When flow exceeds the sewer infrastructure capacity, untreated wastewater enters the natural system by combined sewer overflows. This results in a degradation of the river water quality, depending on the magnitude of the emission and river conditions. Thus, being capable of representing these dynamics in the modelling process is key for a correct assessment of the water quality. In many urbanised hydrological systems the distances between draining sewer infrastructures go beyond the de-correlation length of rainfall processes, especially, for convective summer storms. Hence, spatial and temporal scales of selected rainfall inputs are expected to affect water quality dynamics. The objective of this work is to evaluate how the use of rainfall data from different sources and with different space-time characteristics affects modelled output concentrations of dissolved oxygen in a simplified ICM. The study area is located at the Dommel, a relatively small and sensitive river flowing through the city of Eindhoven (The Netherlands). This river stretch receives the discharge of the 750,000 p.e. WWTP of Eindhoven and from over 200 combined sewer overflows scattered along its length. A pseudo-distributed water quality model has been developed in WEST (mikedhi.com); this is a lumped-physically based model that accounts for urban drainage processes, WWTP and river dynamics for several

The National Water-Quality Assessment (NAWQA) Program planned monitoring and modeling activities for Texas, 2013–23

Science.gov (United States)

Ging, Patricia

2013-01-01

The U.S. Geological Survey’s (USGS) National Water-Quality Assessment (NAWQA) Program was established by Congress in 1992 to answer the following question: What is the status of the Nation’s water quality and is it getting better or worse? Since 1992, NAWQA has been a primary source of nationally consistent data and information on the quality of the Nation’s streams and groundwater. Data and information obtained from objective and nationally consistent water-quality monitoring and modeling activities provide answers to where, when, and why the Nation’s water quality is degraded and what can be done to improve and protect it for human and ecosystem needs. For NAWQA’s third decade (2013–23), a new strategic Science Plan has been developed that describes a strategy for building upon and enhancing the USGS’s ongoing assessment of the Nation’s freshwater quality and aquatic ecosystems.

Mass imbalances in EPANET water-quality simulations

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Davis, Michael J.; Janke, Robert; Taxon, Thomas N.

2018-04-01

EPANET is widely employed to simulate water quality in water distribution systems. However, in general, the time-driven simulation approach used to determine concentrations of water-quality constituents provides accurate results only for short water-quality time steps. Overly long time steps can yield errors in concentration estimates and can result in situations in which constituent mass is not conserved. The use of a time step that is sufficiently short to avoid these problems may not always be feasible. The absence of EPANET errors or warnings does not ensure conservation of mass. This paper provides examples illustrating mass imbalances and explains how such imbalances can occur because of fundamental limitations in the water-quality routing algorithm used in EPANET. In general, these limitations cannot be overcome by the use of improved water-quality modeling practices. This paper also presents a preliminary event-driven approach that conserves mass with a water-quality time step that is as long as the hydraulic time step. Results obtained using the current approach converge, or tend to converge, toward those obtained using the preliminary event-driven approach as the water-quality time step decreases. Improving the water-quality routing algorithm used in EPANET could eliminate mass imbalances and related errors in estimated concentrations. The results presented in this paper should be of value to those who perform water-quality simulations using EPANET or use the results of such simulations, including utility managers and engineers.

Water quality evaluation of Al-Gharraf river by two water quality indices

Science.gov (United States)

Ewaid, Salam Hussein

2017-11-01

Water quality of Al-Gharraf river, the largest branch of Tigris River south of Iraq, was evaluated by the National Sanitation Foundation Water Quality Index (NFS WQI) and the Heavy Metal Pollution Index (HPI) depending on 13 physical, chemical, and biological parameters of water quality measured monthly at ten stations on the river during 2015. The NSF-WQI range obtained for the sampling sites was 61-70 indicating a medium water quality. The HPI value was 98.6 slightly below the critical value for drinking water of 100, and the water quality in the upstream stations is better than downstream due to decrease in water and the accumulation of contaminants along the river. This study explains the significance of applying the water quality indices that show the aggregate impact of ecological factors in charge of water pollution of surface water and which permits translation of the monitoring data to assist the decision makers.

Hydrodynamic modelling of the influence of stormwater and combined sewer overflows on receiving water quality: Benzo(a)pyrene and copper risks to recreational water.

Science.gov (United States)

Björklund, Karin; Bondelind, Mia; Karlsson, Anna; Karlsson, Dick; Sokolova, Ekaterina

2018-02-01

The risk from chemical substances in surface waters is often increased during wet weather, due to surface runoff, combined sewer overflows (CSOs) and erosion of contaminated land. There are strong incentives to improve the quality of surface waters affected by human activities, not only from ecotoxicity and ecosystem health perspectives, but also for drinking water and recreational purposes. The aim of this study is to investigate the influence of urban stormwater discharges and CSOs on receiving water in the context of chemical health risks and recreational water quality. Transport of copper (Cu) and benzo[a]pyrene (BaP) in the Göta River (Sweden) was simulated using a hydrodynamic model. Within the 16 km modelled section, 35 CSO and 16 urban stormwater point discharges, as well as the effluent from a major wastewater treatment plant, were included. Pollutant concentrations in the river were simulated for two rain events and investigated at 13 suggested bathing sites. The simulations indicate that water quality guideline values for Cu are exceeded at several sites, and that stormwater discharges generally give rise to higher Cu and BaP concentrations than CSOs. Due to the location of point discharges and the river current inhibiting lateral mixing, the north shore of the river is better suited for bathing. Peak concentrations have a short duration; increased concentrations of the pollutants may however be present for several days after a rain event. Monitoring of river water quality indicates that simulated Cu and BaP concentrations are in the same order of magnitude as measured concentrations. It is concluded that hydrodynamic modelling is a useful tool for identifying suitable bathing sites in urban surface waters and areas of concern where mitigation measures should be implemented to improve water quality. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial variability analysis of combining the water quality and groundwater flow model to plan groundwater and surface water management in the Pingtung plain

Science.gov (United States)

Chen, Ching-Fang; Chen, Jui-Sheng; Jang, Cheng-Shin

2014-05-01

As a result of rapid economic growth in the Pingtung Plain, the use of groundwater resources has changed dramatically. The groundwater is quite rich in the Pingtung plain and the most important water sources. During the several decades, a substantial amount of groundwater has been pumped for the drinking, irrigation and aquaculture water supplies. However, because the sustainable use concept of groundwater resources is lack, excessive pumping of groundwater causes the occurrence of serious land subsidence and sea water intrusion. Thus, the management and conservation of groundwater resources in the Pingtung plain are considerably critical. This study aims to assess the conjunct use effect of groundwater and surface water in the Pingtung plain on recharge by reducing the amount of groundwater extraction. The groundwater quality variability and groundwater flow models are combined to spatially analyze potential zones of groundwater used for multi-purpose in the Pingtung Plain. First, multivariate indicator kriging (MVIK) is used to analyze spatial variability of groundwater quality based on drinking, aquaculture and irrigation water quality standards, and probabilistically delineate suitable zones in the study area. Then, the groundwater flow model, Processing MODFLOW (PMWIN), is adopted to simulate groundwater flow. The groundwater flow model must be conducted by the calibration and verification processes, and the regional groundwater recovery is discussed when specified water rights are replaced by surface water in the Pingtung plain. Finally, the most suitable zones of reducing groundwater use are determined for multi-purpose according to combining groundwater quality and quantity. The study results can establish a sound and low-impact management plan of groundwater resources utilization for the multi-purpose groundwater use, and prevent decreasing ground water tables, and the occurrence of land subsidence and sea water intrusion in the Pingtung plain.

Multi-objective calibration of a reservoir water quality model in aggregation and non-dominated sorting approaches

Science.gov (United States)

Huang, Yongtai

2014-03-01

Numerical water quality models are developed to predict contaminant fate and transport in receiving waters such as reservoirs and lakes. They can be helpful tools for water resource management. The objective of this study is to calibrate a water quality model which was set up to simulate the water quality conditions of Pepacton Reservoir, Downsville, New York, USA, using an aggregation hybrid genetic algorithm (AHGA) and a non-dominated sorting hybrid genetic algorithm (NSHGA). Both AHGA and NSHGA use a hybrid genetic algorithm (HGA) as optimization engines but are different in fitness assignment. In the AHGA, a weighted sum of scaled simulation errors is designed as an overall objective function to measure the fitness of solutions (i.e., parameter values). In the NSHGA, a method based on non-dominated sorting and Euclidean distances is proposed to calculate the dummy fitness of solutions. In addition, this study also compares the AHGA and the NSHGA. The purpose of this comparison is to determine whether the objective function values (i.e., simulation errors) and simulated results obtained by the AHGA and the NSHGA are significantly different from each other. The results show that the objective function values from the two HGAs are good compromises between all objective functions, and the calibrated model results match the observed data reasonably well and are comparable to other studies, supporting and justifying the use of multi-objective calibration.

NASA-modified precipitation products to improve USEPA nonpoint source water quality modeling for the Chesapeake Bay.

Science.gov (United States)

Nigro, Joseph; Toll, David; Partington, Ed; Ni-Meister, Wenge; Lee, Shihyan; Gutierrez-Magness, Angelica; Engman, Ted; Arsenault, Kristi

2010-01-01

The USEPA has estimated that over 20,000 water bodies within the United States do not meet water quality standards. One of the regulations in the Clean Water Act of 1972 requires states to monitor the total maximum daily load, or the amount of pollution that can be carried by a water body before it is determined to be "polluted," for any watershed in the United States (Copeland, 2005). In response to this mandate, the USEPA developed Better Assessment Science Integrating Nonpoint Sources (BASINS) as a decision support tool for assessing pollution and to guide the decision-making process for improving water quality. One of the models in BASINS, the Hydrological Simulation Program-Fortran (HSPF), computes continuous streamflow rates and pollutant concentration at each basin outlet. By design, precipitation and other meteorological data from weather stations serve as standard model input. In practice, these stations may be unable to capture the spatial heterogeneity of precipitation events, especially if they are few and far between. An attempt was made to resolve this issue by substituting station data with NASA-modified/NOAA precipitation data. Using these data within HSPF, streamflow was calculated for seven watersheds in the Chesapeake Bay Basin during low flow periods, convective storm periods, and annual flows. In almost every case, the modeling performance of HSPF increased when using the NASA-modified precipitation data, resulting in better streamflow statistics and, potentially, in improved water quality assessment.

Water quality control in Third River Reservoir (Argentina using geographical information systems and linear regression models

Directory of Open Access Journals (Sweden)

Claudia Ledesma

2013-08-01

Full Text Available Water quality is traditionally monitored and evaluated based upon field data collected at limited locations. The storage capacity of reservoirs is reduced by deposits of suspended matter. The major factors affecting surface water quality are suspended sediments, chlorophyll and nutrients. Modeling and monitoring the biogeochemical status of reservoirs can be done through data from remote sensors. Since the improvement of sensors’ spatial and spectral resolutions, satellites have been used to monitor the interior areas of bodies of water. Water quality parameters, such as chlorophyll-a concentration and secchi disk depth, were found to have a high correlation with transformed spectral variables derived from bands 1, 2, 3 and 4 of LANDSAT 5TM satellite. We created models of estimated responses in regard to values of chlorophyll-a. To do so, we used population models of single and multiple linear regression, whose parameters are associated with the reflectance data of bands 2 and 4 of the sub-image of the satellite, as well as the data of chlorophyll-a obtained in 25 selected stations. According to the physico-chemical analyzes performed, the characteristics of the water in the reservoir of Rio Tercero, correspond to somewhat hard freshwater with calcium bicarbonate. The water was classified as usable as a source of plant treatment, excellent for irrigation because of its low salinity and low residual sodium carbonate content, but unsuitable for animal consumption because of its low salt content.

An ANN application for water quality forecasting.

Science.gov (United States)

Palani, Sundarambal; Liong, Shie-Yui; Tkalich, Pavel

2008-09-01

Rapid urban and coastal developments often witness deterioration of regional seawater quality. As part of the management process, it is important to assess the baseline characteristics of the marine environment so that sustainable development can be pursued. In this study, artificial neural networks (ANNs) were used to predict and forecast quantitative characteristics of water bodies. The true power and advantage of this method lie in its ability to (1) represent both linear and non-linear relationships and (2) learn these relationships directly from the data being modeled. The study focuses on Singapore coastal waters. The ANN model is built for quick assessment and forecasting of selected water quality variables at any location in the domain of interest. Respective variables measured at other locations serve as the input parameters. The variables of interest are salinity, temperature, dissolved oxygen, and chlorophyll-alpha. A time lag up to 2Delta(t) appeared to suffice to yield good simulation results. To validate the performance of the trained ANN, it was applied to an unseen data set from a station in the region. The results show the ANN's great potential to simulate water quality variables. Simulation accuracy, measured in the Nash-Sutcliffe coefficient of efficiency (R(2)), ranged from 0.8 to 0.9 for the training and overfitting test data. Thus, a trained ANN model may potentially provide simulated values for desired locations at which measured data are unavailable yet required for water quality models.

Collection of Condensate Water: Global Potential and Water Quality Impacts

KAUST Repository

Loveless, Kolin Joseph

2012-12-28

Water is a valuable resource throughout the world, especially in hot, dry climates and regions experiencing significant population growth. Supplies of fresh water are complicated by the economic and political conditions in many of these regions. Technologies that can supply fresh water at a reduced cost are therefore becoming increasingly important and the impact of such technologies can be substantial. This paper considers the collection of condensate water from large air conditioning units as a possible method to alleviate water scarcity issues. Using the results of a climate model that tested data collected from 2000 to 2010, we have identified areas in the world with the greatest collection potential. We gave special consideration to areas with known water scarcities, including the coastal regions of the Arabian Peninsula, Sub-Saharan Africa and South Asia. We found that the quality of the collected water is an important criterion in determining the potential uses for this water. Condensate water samples were collected from a few locations in Saudi Arabia and detailed characterizations were conducted to determine the quality of this water. We found that the quality of condensate water collected from various locations and types of air conditioners was very high with conductivities reaching as low as 18 μS/cm and turbidities of 0. 041 NTU. The quality of the collected condensate was close to that of distilled water and, with low-cost polishing treatments, such as ion exchange resins and electrochemical processes, the condensate quality could easily reach that of potable water. © 2012 Springer Science+Business Media Dordrecht.

An environmental fairness based optimisation model for the decision-support of joint control over the water quantity and quality of a river basin

Science.gov (United States)

Yu, Sen; He, Li; Lu, Hongwei

2016-04-01

This paper presented a new environmental fairness based optimisation model (EFOM) for the decision-support of water resources management and water pollution control at the watershed scale. The model integrated three prediction modules for water consumption and pollutant discharge (WCPD), environmental Gini coefficient (EGC) and water quality (WASP). The model is capable of optimizing the total discharge quantity in the whole basin and controlling units both spatially and temporally, and addressing the conflicts between environmental fairness and efficiency. The model was applied to the Songhua River basin, attempting to support decision-making of joint control over the water quantity and quality. Validation of the WASP module showed that the simulation agreed well with water quality monitoring values (2013) in the Harbin section. Results from the EFOM model also indicated that the water environment in the Harbin section would be improved significantly by effectively controlling the total pollution discharge. The identified optimal strategy obtained from the EFOM showed that the percentage of water in good quality reaches 72% in 2020, suggesting that the strategy would guarantee the planning goals of The China Action Plan for Water Pollution Control to be satisfied. Hence, the modelling under the consideration of environmental fairness can be a new attempt, which is beneficial to optimal joint control of water quantity and water quality at the watershed scale.

Grey fuzzy optimization model for water quality management of a river system

Science.gov (United States)

Karmakar, Subhankar; Mujumdar, P. P.

2006-07-01

A grey fuzzy optimization model is developed for water quality management of river system to address uncertainty involved in fixing the membership functions for different goals of Pollution Control Agency (PCA) and dischargers. The present model, Grey Fuzzy Waste Load Allocation Model (GFWLAM), has the capability to incorporate the conflicting goals of PCA and dischargers in a deterministic framework. The imprecision associated with specifying the water quality criteria and fractional removal levels are modeled in a fuzzy mathematical framework. To address the imprecision in fixing the lower and upper bounds of membership functions, the membership functions themselves are treated as fuzzy in the model and the membership parameters are expressed as interval grey numbers, a closed and bounded interval with known lower and upper bounds but unknown distribution information. The model provides flexibility for PCA and dischargers to specify their aspirations independently, as the membership parameters for different membership functions, specified for different imprecise goals are interval grey numbers in place of a deterministic real number. In the final solution optimal fractional removal levels of the pollutants are obtained in the form of interval grey numbers. This enhances the flexibility and applicability in decision-making, as the decision-maker gets a range of optimal solutions for fixing the final decision scheme considering technical and economic feasibility of the pollutant treatment levels. Application of the GFWLAM is illustrated with case study of the Tunga-Bhadra river system in India.

Abnormal quality detection and isolation in water distribution networks using simulation models

Directory of Open Access Journals (Sweden)

F. Nejjari

2012-11-01

Full Text Available This paper proposes a model based detection and localisation method to deal with abnormal quality levels based on the chlorine measurements and chlorine sensitivity analysis in a water distribution network. A fault isolation algorithm which correlates on line the residuals (generated by comparing the available chlorine measurements with their estimations using a model with the fault sensitivity matrix is used. The proposed methodology has been applied to a District Metered Area (DMA in the Barcelona network.

Use of ocean color scanner data in water quality mapping

Science.gov (United States)

Khorram, S.

1981-01-01

Remotely sensed data, in combination with in situ data, are used in assessing water quality parameters within the San Francisco Bay-Delta. The parameters include suspended solids, chlorophyll, and turbidity. Regression models are developed between each of the water quality parameter measurements and the Ocean Color Scanner (OCS) data. The models are then extended to the entire study area for mapping water quality parameters. The results include a series of color-coded maps, each pertaining to one of the water quality parameters, and the statistical analysis of the OCS data and regression models. It is found that concurrently collected OCS data and surface truth measurements are highly useful in mapping the selected water quality parameters and locating areas having relatively high biological activity. In addition, it is found to be virtually impossible, at least within this test site, to locate such areas on U-2 color and color-infrared photography.

Extending a Consensus-based Fuzzy Ordered Weighting Average (FOWA Model in New Water Quality Indices

Directory of Open Access Journals (Sweden)

Mohammad Ali Baghapour

2017-07-01

Full Text Available In developing a specific WQI (Water Quality Index, many quality parameters are involved with different levels of importance. The impact of experts’ different opinions and viewpoints, current risks affecting their opinions, and plurality of the involved parameters double the significance of the issue. Hence, the current study tries to apply a consensus-based FOWA (Fuzzy Ordered Weighting Average model as one of the most powerful and well-known Multi-Criteria Decision- Making (MCDM techniques to determine the importance of the used parameters in the development of such WQIs which is shown with an example. This operator has provided the capability of modeling the risks in decision-making through applying the optimistic degree of stakeholders and their power coupled with the use of fuzzy numbers. Totally, 22 water quality parameters for drinking purposes were considered in this study. To determine the weight of each parameter, the viewpoints of 4 decision-making groups of experts were taken into account. After determining the final weights, to validate the use of each parameter in a potential WQI, consensus degrees of both the decision makers and the parameters are calculated. The highest and the lowest weight values, 0.999 and 0.073 respectively, were related to Hg and temperature. Regarding the type of consumption that was drinking, the parameters’ weights and ranks were consistent with their health impacts. Moreover, the decision makers’ highest and lowest consensus degrees were 0.9905 and 0.9669, respectively. Among the water quality parameters, temperature (with consensus degree of 0.9972 and Pb (with consensus degree of 0.9665, received the highest and lowest agreement with the decision-making group. This study indicated that the weight of parameters in determining water quality largely depends on the experts’ opinions and approaches. Moreover, using the FOWA model provides results accurate and closer- to-reality on the significance of

Monitoring water quality in a hypereutrophic reservoir using Landsat ETM+ and OLI sensors: how transferable are the water quality algorithms?

Science.gov (United States)

Deutsch, Eliza S; Alameddine, Ibrahim; El-Fadel, Mutasem

2018-02-15

The launch of the Landsat 8 in February 2013 extended the life of the Landsat program to over 40 years, increasing the value of using Landsat to monitor long-term changes in the water quality of small lakes and reservoirs, particularly in poorly monitored freshwater systems. Landsat-based water quality hindcasting often incorporate several Landsat sensors in an effort to increase the temporal range of observations; yet the transferability of water quality algorithms across sensors remains poorly examined. In this study, several empirical algorithms were developed to quantify chlorophyll-a, total suspended matter (TSM), and Secchi disk depth (SDD) from surface reflectance measured by Landsat 7 ETM+ and Landsat 8 OLI sensors. Sensor-specific multiple linear regression models were developed by correlating in situ water quality measurements collected from a semi-arid eutrophic reservoir with band ratios from Landsat ETM+ and OLI sensors, along with ancillary data (water temperature and seasonality) representing ecological patterns in algae growth. Overall, ETM+-based models outperformed (adjusted R 2 chlorophyll-a = 0.70, TSM = 0.81, SDD = 0.81) their OLI counterparts (adjusted R 2 chlorophyll-a = 0.50, TSM = 0.58, SDD = 0.63). Inter-sensor differences were most apparent for algorithms utilizing the Blue spectral band. The inclusion of water temperature and seasonality improved the power of TSM and SDD models.

Are our dynamic water quality models too complex? A comparison of a new parsimonious phosphorus model, SimplyP, and INCA-P

Science.gov (United States)

Jackson-Blake, L. A.; Sample, J. E.; Wade, A. J.; Helliwell, R. C.; Skeffington, R. A.

2017-07-01

Catchment-scale water quality models are increasingly popular tools for exploring the potential effects of land management, land use change and climate change on water quality. However, the dynamic, catchment-scale nutrient models in common usage are complex, with many uncertain parameters requiring calibration, limiting their usability and robustness. A key question is whether this complexity is justified. To explore this, we developed a parsimonious phosphorus model, SimplyP, incorporating a rainfall-runoff model and a biogeochemical model able to simulate daily streamflow, suspended sediment, and particulate and dissolved phosphorus dynamics. The model's complexity was compared to one popular nutrient model, INCA-P, and the performance of the two models was compared in a small rural catchment in northeast Scotland. For three land use classes, less than six SimplyP parameters must be determined through calibration, the rest may be based on measurements, while INCA-P has around 40 unmeasurable parameters. Despite substantially simpler process-representation, SimplyP performed comparably to INCA-P in both calibration and validation and produced similar long-term projections in response to changes in land management. Results support the hypothesis that INCA-P is overly complex for the study catchment. We hope our findings will help prompt wider model comparison exercises, as well as debate among the water quality modeling community as to whether today's models are fit for purpose. Simpler models such as SimplyP have the potential to be useful management and research tools, building blocks for future model development (prototype code is freely available), or benchmarks against which more complex models could be evaluated.

Managing water quality under drought conditions in the Llobregat River Basin.

Science.gov (United States)

Momblanch, Andrea; Paredes-Arquiola, Javier; Munné, Antoni; Manzano, Andreu; Arnau, Javier; Andreu, Joaquín

2015-01-15

The primary effects of droughts on river basins include both depleted quantity and quality of the available water resources, which can render water resources useless for human needs and simultaneously damage the environment. Isolated water quality analyses limit the action measures that can be proposed. Thus, an integrated evaluation of water management and quality is warranted. In this study, a methodology consisting of two coordinated models is used to combine aspects of water resource allocation and water quality assessment. Water management addresses water allocation issues by considering the storage, transport and consumption elements. Moreover, the water quality model generates time series of concentrations for several pollutants according to the water quality of the runoff and the demand discharges. These two modules are part of the AQUATOOL decision support system shell for water resource management. This tool facilitates the analysis of the effects of water management and quality alternatives and scenarios on the relevant variables in a river basin. This paper illustrates the development of an integrated model for the Llobregat River Basin. The analysis examines the drought from 2004 to 2008, which is an example of a period when the water system was quantitative and qualitatively stressed. The performed simulations encompass a wide variety of water management and water quality measures; the results provide data for making informed decisions. Moreover, the results demonstrated the importance of combining these measures depending on the evolution of a drought event and the state of the water resources system. Copyright © 2014 Elsevier B.V. All rights reserved.

Application of Water Quality Model of Jordan River to Evaluate Climate Change Effects on Eutrophication

Science.gov (United States)

Van Grouw, B.

2016-12-01

The Jordan River is a 51 mile long freshwater stream in Utah that provides drinking water to more than 50% of Utah's population. The various point and nonpoint sources introduce an excess of nutrients into the river. This excess induces eutrophication that results in an inhabitable environment for aquatic life is expected to be exacerbated due to climate change. Adaptive measures must be evaluated based on predictions of climate variation impacts on eutrophication and ecosystem processes in the Jordan River. A Water Quality Assessment Simulation Program (WASP) model was created to analyze the data results acquired from a Total Maximum Daily Load (TMDL) study conducted on the Jordan River. Eutrophication is modeled based on levels of phosphates and nitrates from point and nonpoint sources, temperature, and solar radiation. It will simulate the growth of phytoplankton and periphyton in the river. This model will be applied to assess how water quality in the Jordan River is affected by variations in timing and intensity of spring snowmelt and runoff during drought in the valley and the resulting effects on eutrophication in the river.

NASA-Modified Precipitation Products to Improve EPA Nonpoint Source Water Quality Modeling for the Chesapeake Bay

Science.gov (United States)

Nigro, Joseph; Toll, David; Partington, Ed; Ni-Meister, Wenge; Lee, Shihyan; Gutierrez-Magness, Angelica; Engman, Ted; Arsenault, Kristi

2010-01-01

The Environmental Protection Agency (EPA) has estimated that over 20,000 water bodies within the United States do not meet water quality standards. Ninety percent of the impairments are typically caused by nonpoint sources. One of the regulations in the Clean Water Act of 1972 requires States to monitor the Total Maximum Daily Load (TMDL), or the amount of pollution that can be carried by a water body before it is determined to be "polluted", for any watershed in the U.S.. In response to this mandate, the EPA developed Better Assessment Science Integrating Nonpoint Sources (BASINS) as a Decision Support Tool (DST) for assessing pollution and to guide the decision making process for improving water quality. One of the models in BASINS, the Hydrological Simulation Program -- Fortran (HSPF), computes daily stream flow rates and pollutant concentration at each basin outlet. By design, precipitation and other meteorological data from weather stations serve as standard model input. In practice, these stations may be unable to capture the spatial heterogeneity of precipitation events especially if they are few and far between. An attempt was made to resolve this issue by substituting station data with NASA modified/NOAA precipitation data. Using these data within HSPF, stream flow was calculated for seven watersheds in the Chesapeake Bay Basin during low flow periods, convective storm periods, and annual flows. In almost every case, the modeling performance of HSPF increased when using the NASA-modified precipitation data, resulting in better stream flow statistics and, ultimately, in improved water quality assessment.

Simplifying dynamic river water quality modelling: A case study of inorganic nitrogen dynamics in the Crocodile River (South Africa).

CSIR Research Space (South Africa)

Deksissa, T

2004-06-01

Full Text Available Quality Model No. 1, which is one of the most comprehensive basic river water quality models available in literature. The applicability of the simplified model in data limited situations was investigated using a case study of inorganic nitrogen (nitrate...

Stressor-response modeling using the 2D water quality model and regression trees to predict chlorophyll-a in a reservoir system

Science.gov (United States)

In order to control algal blooms, stressor-response relationships between water quality metrics, environmental variables, and algal growth should be understood and modeled. Machine-learning methods were suggested to express stressor-response relationships found by application of mechanistic water qu...

Numerical simulation of water quality in Yangtze Estuary

Directory of Open Access Journals (Sweden)

Xi Li

2009-12-01

Full Text Available In order to monitor water quality in the Yangtze Estuary, water samples were collected and field observation of current and velocity stratification was carried out using a shipboard acoustic Doppler current profiler (ADCP. Results of two representative variables, the temporal and spatial variation of new point source sewage discharge as manifested by chemical oxygen demand (COD and the initial water quality distribution as manifested by dissolved oxygen (DO, were obtained by application of the Environmental Fluid Dynamics Code (EFDC with solutions for hydrodynamics during tides. The numerical results were compared with field data, and the field data provided verification of numerical application: this numerical model is an effective tool for water quality simulation. For point source discharge, COD concentration was simulated with an initial value in the river of zero. The simulated increments and distribution of COD in the water show acceptable agreement with field data. The concentration of DO is much higher in the North Branch than in the South Branch due to consumption of oxygen in the South Branch resulting from discharge of sewage from Shanghai. The DO concentration is greater in the surface layer than in the bottom layer. The DO concentration is low in areas with a depth of less than 20 m, and high in areas between the 20-m and 30-m isobaths. It is concluded that the numerical model is valuable in simulation of water quality in the case of specific point source pollutant discharge. The EFDC model is also of satisfactory accuracy in water quality simulation of the Yangtze Estuary.

The EDEN-IW ontology model for sharing knowledge and water quality data between heterogenous databases

DEFF Research Database (Denmark)

Stjernholm, M.; Poslad, S.; Zuo, L.

2004-01-01

The Environmental Data Exchange Network for Inland Water (EDEN-IW) project's main aim is to develop a system for making disparate and heterogeneous databases of Inland Water quality more accessible to users. The core technology is based upon a combination of: ontological model to represent...... a Semantic Web based data model for IW; software agents as an infrastructure to share and reason about the IW se-mantic data model and XML to make the information accessible to Web portals and mainstream Web services. This presentation focuses on the Semantic Web or Onto-logical model. Currently, we have...

Development and assessment of an integrated ecological modelling framework to assess the effect of investments in wastewater treatment on water quality.

Science.gov (United States)

Holguin-Gonzalez, Javier E; Boets, Pieter; Everaert, Gert; Pauwels, Ine S; Lock, Koen; Gobeyn, Sacha; Benedetti, Lorenzo; Amerlinck, Youri; Nopens, Ingmar; Goethals, Peter L M

2014-01-01

Worldwide, large investments in wastewater treatment are made to improve water quality. However, the impacts of these investments on river water quality are often not quantified. To assess water quality, the European Water Framework Directive (WFD) requires an integrated approach. The aim of this study was to develop an integrated ecological modelling framework for the River Drava (Croatia) that includes physical-chemical and hydromorphological characteristics as well as the ecological river water quality status. The developed submodels and the integrated model showed accurate predictions when comparing the modelled results to the observations. Dissolved oxygen and nitrogen concentrations (ammonium and organic nitrogen) were the most important variables in determining the ecological water quality (EWQ). The result of three potential investment scenarios of the wastewater treatment infrastructure in the city of Varaždin on the EWQ of the River Drava was assessed. From this scenario-based analysis, it was concluded that upgrading the existing wastewater treatment plant with nitrogen and phosphorus removal will be insufficient to reach a good EWQ. Therefore, other point and diffuse pollution sources in the area should also be monitored and remediated to meet the European WFD standards.

Effects of temporal and spatial resolution of calibration data on integrated hydrologic water quality model identification

Science.gov (United States)

Jiang, Sanyuan; Jomaa, Seifeddine; Büttner, Olaf; Rode, Michael

2014-05-01

Hydrological water quality modeling is increasingly used for investigating runoff and nutrient transport processes as well as watershed management but it is mostly unclear how data availablity determins model identification. In this study, the HYPE (HYdrological Predictions for the Environment) model, which is a process-based, semi-distributed hydrological water quality model, was applied in two different mesoscale catchments (Selke (463 km2) and Weida (99 km2)) located in central Germany to simulate discharge and inorganic nitrogen (IN) transport. PEST and DREAM(ZS) were combined with the HYPE model to conduct parameter calibration and uncertainty analysis. Split-sample test was used for model calibration (1994-1999) and validation (1999-2004). IN concentration and daily IN load were found to be highly correlated with discharge, indicating that IN leaching is mainly controlled by runoff. Both dynamics and balances of water and IN load were well captured with NSE greater than 0.83 during validation period. Multi-objective calibration (calibrating hydrological and water quality parameters simultaneously) was found to outperform step-wise calibration in terms of model robustness. Multi-site calibration was able to improve model performance at internal sites, decrease parameter posterior uncertainty and prediction uncertainty. Nitrogen-process parameters calibrated using continuous daily averages of nitrate-N concentration observations produced better and more robust simulations of IN concentration and load, lower posterior parameter uncertainty and IN concentration prediction uncertainty compared to the calibration against uncontinuous biweekly nitrate-N concentration measurements. Both PEST and DREAM(ZS) are efficient in parameter calibration. However, DREAM(ZS) is more sound in terms of parameter identification and uncertainty analysis than PEST because of its capability to evolve parameter posterior distributions and estimate prediction uncertainty based on global

Time-scale Dependence of Response of an Estuarine Water Quality Model to Nutrient Loading

Science.gov (United States)

We describe calibration and evaluation of a water quality model being implemented for Narragansett Bay to quantify the response of concentrations of nutrients, phytoplankton chlorophyll a and dissolved oxygen in the Bay to loading rates of nutrients and other boundary conditions....

CHARACTERIZING PIPE WALL DEMAND: IMPLICATIONS FOR WATER QUALITY MODELING

Science.gov (United States)

It has become generally accepted that water quality can deteriorate in a distribution system through reactions in the bulk phase and/or at the pipe wall. These reactions may be physical, chemical or microbiological in nature. Perhaps one of the most serious aspects of water qua...

Water availability, water quality water governance: the future ahead

Science.gov (United States)

Tundisi, J. G.; Matsumura-Tundisi, T.; Ciminelli, V. S.; Barbosa, F. A.

2015-04-01

The major challenge for achieving a sustainable future for water resources and water security is the integration of water availability, water quality and water governance. Water is unevenly distributed on Planet Earth and these disparities are cause of several economic, ecological and social differences in the societies of many countries and regions. As a consequence of human misuse, growth of urbanization and soil degradation, water quality is deteriorating continuously. Key components for the maintenance of water quantity and water quality are the vegetation cover of watersheds, reduction of the demand and new water governance that includes integrated management, predictive evaluation of impacts, and ecosystem services. Future research needs are discussed.

River water quality model no. 1 (RWQM1): II. Biochemical process equations

DEFF Research Database (Denmark)

Reichert, P.; Borchardt, D.; Henze, Mogens

2001-01-01

In this paper, biochemical process equations are presented as a basis for water quality modelling in rivers under aerobic and anoxic conditions. These equations are not new, but they summarise parts of the development over the past 75 years. The primary goals of the presentation are to stimulate...... transformation processes. This paper is part of a series of three papers. In the first paper, the general modelling approach is described; in the present paper, the biochemical process equations of a complex model are presented; and in the third paper, recommendations are given for the selection of a reasonable...

CE–QUAL–W2 water-quality model and supporting LOADEST models for Lake St. Croix, Wisconsin and Minnesota, 2013

Data.gov (United States)

Department of the Interior — A mechanistic, biophysical water-quality model (CE–QUAL–W2) was developed and calibrated for Lake St. Croix, Wisconsin and Minnesota. The Lake St. Croix CE–QUAL–W2...

The economics of water reuse and implications for joint water quality-quantity management

Science.gov (United States)

Kuwayama, Y.

2015-12-01

Traditionally, economists have treated the management of water quality and water quantity as separate problems. However, there are some water management issues for which economic analysis requires the simultaneous consideration of water quality and quantity policies and outcomes. Water reuse, which has expanded significantly over the last several decades, is one of these issues. Analyzing the cost effectiveness and social welfare outcomes of adopting water reuse requires a joint water quality-quantity optimization framework because, at its most basic level, water reuse requires decision makers to consider (a) its potential for alleviating water scarcity, (b) the quality to which the water should be treated prior to reuse, and (c) the benefits of discharging less wastewater into the environment. In this project, we develop a theoretical model of water reuse management to illustrate how the availability of water reuse technologies and practices can lead to a departure from established rules in the water resource economics literature for the optimal allocation of freshwater and water pollution abatement. We also conduct an econometric analysis of a unique dataset of county-level water reuse from the state of Florida over the seventeen-year period between 1996 and 2012 in order to determine whether water quality or scarcity concerns drive greater adoption of water reuse practices.

Statistical Framework for Recreational Water Quality Criteria and Monitoring

DEFF Research Database (Denmark)

Halekoh, Ulrich

2008-01-01

recreational governmental authorities controlling water quality. The book opens with a historical account of water quality criteria in the USA between 1922 and 2003. Five chapters are related to sampling strategies and decision rules. Chapter 2 discusses the dependence of decision-making rules on short...... modeling exploiting additional information like meteorological data can support the decision process as shown in Chapter 10. The question of which information to extract from water sample analyses is closely related to the task of risk assessment for human health. Beach-water quality is often measured......Administrators of recreational waters face the basic tasks of surveillance of water quality and decisions on beach closure in case of unacceptable quality. Monitoring and subsequent decisions are based on sampled water probes and fundamental questions are which type of data to extract from...

A spatially distributed model for assessment of the effects of changing land use and climate on urban stream quality: Development of a Spatially Distributed Urban Water Quality Model

Energy Technology Data Exchange (ETDEWEB)

Sun, Ning [Department of Civil and Environmental Engineering, University of Washington, Seattle WA USA; Pacific Northwest National Laboratory, Richland WA USA; Yearsley, John [Department of Civil and Environmental Engineering, University of Washington, Seattle WA USA; Baptiste, Marisa [Department of Civil and Environmental Engineering, University of Washington, Seattle WA USA; Cao, Qian [Department of Geography, University of California Los Angeles, Los Angeles CA USA; Lettenmaier, Dennis P. [Department of Geography, University of California Los Angeles, Los Angeles CA USA; Nijssen, Bart [Department of Civil and Environmental Engineering, University of Washington, Seattle WA USA

2016-08-22

While the effects of land use change in urban areas have been widely examined, the combined effects of climate and land use change on the quality of urban and urbanizing streams have received much less attention. We describe a modeling framework that is applicable to the evaluation of potential changes in urban water quality and associated hydrologic changes in response to ongoing climate and landscape alteration. The grid-based spatially distributed model, DHSVM-WQ, is an outgrowth of the Distributed Hydrology-Soil-Vegetation Model (DHSVM) that incorporates modules for assessing hydrology and water quality in urbanized watersheds at a high spatial and temporal resolution. DHSVM-WQ simulates surface runoff quality and in-stream processes that control the transport of nonpoint-source (NPS) pollutants into urban streams. We configure DHSVM-WQ for three partially urbanized catchments in the Puget Sound region to evaluate the water quality responses to current conditions and projected changes in climate and/or land use over the next century. Here we focus on total suspended solids (TSS) and total phosphorus (TP) from nonpoint sources (runoff), as well as stream temperature. The projection of future land use is characterized by a combination of densification in existing urban or partially urban areas, and expansion of the urban footprint. The climate change scenarios consist of individual and concurrent changes in temperature and precipitation. Future precipitation is projected to increase in winter and decrease in summer, while future temperature is projected to increase throughout the year. Our results show that urbanization has a much greater effect than climate change on both the magnitude and seasonal variability of streamflow, TSS and TP loads largely due to substantially increased streamflow, and particularly winter flow peaks. Water temperature is more sensitive to climate warming scenarios than to urbanization and precipitation changes. Future urbanization and

Water Quality Vocabulary Development and Deployment

Science.gov (United States)

Simons, B. A.; Yu, J.; Cox, S. J.

2013-12-01

Semantic descriptions of observed properties and associated units of measure are fundamental to understanding of environmental observations, including groundwater, surface water and marine water quality. Semantic descriptions can be captured in machine-readable ontologies and vocabularies, thus providing support for the annotation of observation values from the disparate data sources with appropriate and accurate metadata, which is critical for achieving semantic interoperability. However, current stand-alone water quality vocabularies provide limited support for cross-system comparisons or data fusion. To enhance semantic interoperability, the alignment of water-quality properties with definitions of chemical entities and units of measure in existing widely-used vocabularies is required. Modern ontologies and vocabularies are expressed, organized and deployed using Semantic Web technologies. We developed an ontology for observed properties (i.e. a model for expressing appropriate controlled vocabularies) which extends the NASA/TopQuadrant QUDT ontology for Unit and QuantityKind with two additional classes and two properties (see accompanying paper by Cox, Simons and Yu). We use our ontology to populate the Water Quality vocabulary with a set of individuals of each of the four key classes (and their subclasses), and add appropriate relationships between these individuals. This ontology is aligned with other relevant stand-alone Water Quality vocabularies and domain ontologies. Developing the Water Quality vocabulary involved two main steps. First, the Water Quality vocabulary was populated with individuals of the ObservedProperty class, which was determined from a census of existing datasets and services. Each ObservedProperty individual relates to other individuals of Unit and QuantityKind (taken from QUDT where possible), and to IdentifiedObject individuals. As a large fraction of observed water quality data are classified by the chemical substance involved, the

Resource modelling for control: how hydrogeological modelling can support a water quality monitoring infrastructure

Science.gov (United States)

Scozzari, Andrea; Doveri, Marco

2015-04-01

The knowledge of the physical/chemical processes implied with the exploitation of water bodies for human consumption is an essential tool for the optimisation of the monitoring infrastructure. Due to their increasing importance in the context of human consumption (at least in the EU), this work focuses on groundwater resources. In the framework of drinkable water networks, the physical and data-driven modelling of transport phenomena in groundwater can help optimising the sensor network and validating the acquired data. This work proposes the combined usage of physical and data-driven modelling as a support to the design and maximisation of results from a network of distributed sensors. In particular, the validation of physico-chemical measurements and the detection of eventual anomalies by a set of continuous measurements take benefit from the knowledge of the domain from which water is abstracted, and its expected characteristics. Change-detection techniques based on non-specific sensors (presented by quite a large literature during the last two decades) have to deal with the classical issues of maximising correct detections and minimising false alarms, the latter of the two being the most typical problem to be faced, in the view of designing truly applicable monitoring systems. In this context, the definition of "anomaly" in terms of distance from an expected value or feature characterising the quality of water implies the definition of a suitable metric and the knowledge of the physical and chemical peculiarities of the natural domain from which water is exploited, with its implications in terms of characteristics of the water resource.

Water Quality Criteria

Science.gov (United States)

EPA develops water quality criteria based on the latest scientific knowledge to protect human health and aquatic life. This information serves as guidance to states and tribes in adopting water quality standards.

A Bayesian approach for evaluation of the effect of water quality model parameter uncertainty on TMDLs: A case study of Miyun Reservoir

International Nuclear Information System (INIS)

Liang, Shidong; Jia, Haifeng; Xu, Changqing; Xu, Te; Melching, Charles

2016-01-01

Facing increasingly serious water pollution, the Chinese government is changing the environmental management strategy from solely pollutant concentration control to a Total Maximum Daily Load (TMDL) program, and water quality models are increasingly being applied to determine the allowable pollutant load in the TMDL. Despite the frequent use of models, few studies have focused on how parameter uncertainty in water quality models affect the allowable pollutant loads in the TMDL program, particularly for complicated and high-dimension water quality models. Uncertainty analysis for such models is limited by time-consuming simulation and high-dimensionality and nonlinearity in parameter spaces. In this study, an allowable pollutant load calculation platform was established using the Environmental Fluid Dynamics Code (EFDC), which is a widely applied hydrodynamic-water quality model. A Bayesian approach, i.e. the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm, which is a high-efficiency, multi-chain Markov Chain Monte Carlo (MCMC) method, was applied to assess the effects of parameter uncertainty on the water quality model simulations and its influence on the allowable pollutant load calculation in the TMDL program. Miyun Reservoir, which is the most important surface drinking water source for Beijing, suffers from eutrophication and was selected as a case study. The relations between pollutant loads and water quality indicators are obtained through a graphical method in the simulation platform. Ranges of allowable pollutant loads were obtained according to the results of parameter uncertainty analysis, i.e. Total Organic Carbon (TOC): 581.5–1030.6 t·yr"−"1; Total Phosphorus (TP): 23.3–31.0 t·yr"−"1; and Total Nitrogen (TN): 480–1918.0 t·yr"−"1. The wide ranges of allowable pollutant loads reveal the importance of parameter uncertainty analysis in a TMDL program for allowable pollutant load calculation and margin of safety (MOS

Modelling microbiological water quality in the Seine river drainage network: past, present and future situations

Directory of Open Access Journals (Sweden)

P. Servais

2007-09-01

Full Text Available The Seine river watershed is characterized by a high population density and intense agricultural activities. Data show low microbiological water quality in the main rivers (Seine, Marne, Oise of the watershed. Today, there is an increasing pressure from different social groups to restore microbiological water quality in order to both increase the safety of drinking water production and to restore the possible use of these rivers for bathing and rowing activities, as they were in the past. A model, appended to the hydro-ecological SENEQUE/Riverstrahler model describing the functioning of large river systems, was developed to describe the dynamics of faecal coliforms (FC, the most usual faecal contamination indicator. The model is able to calculate the distribution of FC concentrations in the whole drainage network resulting from land use and wastewater management in the watershed. The model was validated by comparing calculated FC concentrations with available field data for some well-documented situations in different river stretches of the Seine drainage network. Once validated, the model was used to test various predictive scenarios, as, for example, the impact of the modifications in wastewater treatment planned at the 2012 horizon in the Seine watershed in the scope of the implementation of the european water framework directive. The model was also used to investigate past situations. In particular, the variations of the microbiological water quality in the Parisian area due to population increase and modifications in wastewater management were estimated over the last century. It was shown that the present standards for bathing and other aquatic recreational activities are not met in the large tributaries upstream from Paris since the middle of the 1950's, and at least since the middle of the XIXth century in the main branch of the Seine river downstream from Paris. Efforts carried out for improving urban wastewater treatment in terms

Hydroeconomic optimization of reservoir management under downstream water quality constraints

DEFF Research Database (Denmark)

Davidsen, Claus; Liu, Suxia; Mo, Xingguo

2015-01-01

water quantity and water quality management and minimizes the total costs over a planning period assuming stochastic future runoff. The outcome includes cost-optimal reservoir releases, groundwater pumping, water allocation, wastewater treatments and water curtailments. The optimization model uses......), and the resulting minimum dissolved oxygen (DO) concentration is computed with the Streeter-Phelps equation and constrained to match Chinese water quality targets. The baseline water scarcity and operational costs are estimated to 15.6. billion. CNY/year. Compliance to water quality grade III causes a relatively...

78 FR 20252 - Water Quality Standards; Withdrawal of Certain Federal Water Quality Criteria Applicable to...

Science.gov (United States)

2013-04-04

... Water Quality Standards; Withdrawal of Certain Federal Water Quality Criteria Applicable to California... aquatic life water quality criteria applicable to waters of New Jersey, Puerto Rico, and California's San Francisco Bay. In 1992, EPA promulgated the National Toxics Rule or NTR to establish numeric water quality...

Quality control in public participation assessments of water quality: the OPAL Water Survey.

Science.gov (United States)

Rose, N L; Turner, S D; Goldsmith, B; Gosling, L; Davidson, T A

2016-07-22

Public participation in scientific data collection is a rapidly expanding field. In water quality surveys, the involvement of the public, usually as trained volunteers, generally includes the identification of aquatic invertebrates to a broad taxonomic level. However, quality assurance is often not addressed and remains a key concern for the acceptance of publicly-generated water quality data. The Open Air Laboratories (OPAL) Water Survey, launched in May 2010, aimed to encourage interest and participation in water science by developing a 'low-barrier-to-entry' water quality survey. During 2010, over 3000 participant-selected lakes and ponds were surveyed making this the largest public participation lake and pond survey undertaken to date in the UK. But the OPAL approach of using untrained volunteers and largely anonymous data submission exacerbates quality control concerns. A number of approaches were used in order to address data quality issues including: sensitivity analysis to determine differences due to operator, sampling effort and duration; direct comparisons of identification between participants and experienced scientists; the use of a self-assessment identification quiz; the use of multiple participant surveys to assess data variability at single sites over short periods of time; comparison of survey techniques with other measurement variables and with other metrics generally considered more accurate. These quality control approaches were then used to screen the OPAL Water Survey data to generate a more robust dataset. The OPAL Water Survey results provide a regional and national assessment of water quality as well as a first national picture of water clarity (as suspended solids concentrations). Less than 10 % of lakes and ponds surveyed were 'poor' quality while 26.8 % were in the highest water quality band. It is likely that there will always be a question mark over untrained volunteer generated data simply because quality assurance is uncertain

Environmetric data interpretation to assess surface water quality

International Nuclear Information System (INIS)

Simeonova, P.; Papazova, P.; Lovchinov, V.

2013-01-01

Two multivariate statistical methods (Cluster analysis /CA/ and Principal components analysis /PCA/) were applied for model assessment of the water quality of Maritsa River and Tundja River on Bulgarian territory. The study used long-term monitoring data from many sampling sites characterized by various surface water quality indicators. The application of CA to the indicators results in formation of clusters showing the impact of biological, anthropogenic and eutrophication sources. For further assessment of the monitoring data, PCA was implemented, which identified, again, latent factors confirming, in principle, the clustering output. Their identification coincide correctly to the location of real pollution sources along the rivers catchments. The linkage of the sampling sites along the river flow by CA identified several special patterns separated by specific tracers levels. The apportionment models of the pollution determined the contribution of each one of identified pollution factors to the total concentration of each one of the water quality parameters. Thus, a better risk management of the surface water quality is achieved both on local and national level

Effects of Changes in Lugu Lake Water Quality on Schizothorax Yunnansis Ecological Habitat Based on HABITAT Model

Science.gov (United States)

Huang, Wei; Mynnet, Arthur

Schizothorax Yunnansis is an unique fish species only existing in Lugu Lake, which is located in the southwestern China. The simulation and research on Schizothorax Yunnansis habitat environment have a vital significance to protect this rare fish. With the development of the tourism industry, there bring more pressure on the environmental protection. The living environment of Schizothorax Yunnansis is destroyed seriously because the water quality is suffering the sustaining pollution of domestic sewage from the peripheral villages. This paper analyzes the relationship between water quality change and Schizothorax Yunnansis ecological habitat and evalutes Schizothorax Yunnansis's ecological habitat impact based on HABITAT model. The results show that when the TP concentration in Lugu Lake does not exceed Schizothorax Yunnansis's survival threshold, Schizothorax Yunnansis can get more nutrients and the suitable habitat area for itself is increased. Conversely, it can lead to TP toxicity in the Schizothorax Yunnansis and even death. Therefore, unsuitable habitat area for Schizothorax Yunnansis is increased. It can be seen from the results that HABITAT model can assist in ecological impact assessment studies by translating results of hydrological, water quality models into effects on the natural environment and human society.

Kansas environmental and resource study: A Great Plains model. Monitoring fresh water resources. [water quality of reservoirs

Science.gov (United States)

Yarger, H. L. (Principal Investigator); Mccauley, J. R.

1974-01-01

The author has identified the following significant results. Processing and analysis of CCT's for numerous ground truth supported passes over Kansas reservoirs has demonstrated that sun angle and atmospheric conditions are strong influences on water reflectance levels as detected by ERTS-1 and can suppress the contributions of true water quality factors. Band ratios, on the other hand, exhibit very little dependence on sun angle and sky conditions and thus are more directly related to water quality. Band ratio levels can be used to reliably determine suspended load. Other water quality indicators appear to have little or no affect on reflectance levels.

Application of Hyperspectral Remote Sensing Techniques to Evaluate Water Quality in Turbid Coastal Waters of South Carolina.

Science.gov (United States)

Ali, K. A.; Ryan, K.

2014-12-01

Coastal and inland waters represent a diverse set of resources that support natural habitat and provide valuable ecosystem services to the human population. Conventional techniques to monitor water quality using in situ sensors and laboratory analysis of water samples can be very time- and cost-intensive. Alternatively, remote sensing techniques offer better spatial coverage and temporal resolution to accurately characterize the dynamic and unique water quality parameters. Existing remote sensing ocean color products, such as the water quality proxy chlorophyll-a, are based on ocean derived bio-optical models that are primarily calibrated in Case 1 type waters. These traditional models fail to work when applied in turbid (Case 2 type), coastal waters due to spectral interference from other associated color producing agents such as colored dissolved organic matter and suspended sediments. In this work, we introduce a novel technique for the predictive modeling of chlorophyll-a using a multivariate-based approach applied to in situ hyperspectral radiometric data collected from the coastal waters of Long Bay, South Carolina. This method uses a partial least-squares regression model to identify prominent wavelengths that are more sensitive to chlorophyll-a relative to other associated color-producing agents. The new model was able to explain 80% of the observed chlorophyll-a variability in Long Bay with RMSE = 2.03 μg/L. This approach capitalizes on the spectral advantage gained from current and future hyperspectral sensors, thus providing a more robust predicting model. This enhanced mode of water quality monitoring in marine environments will provide insight to point-sources and problem areas that may contribute to a decline in water quality. The utility of this tool is in its versatility to a diverse set of coastal waters and its use by coastal and fisheries managers with regard to recreation, regulation, economic and public health purposes.

Simulation of water quality for Salt Creek in northeastern Illinois

Science.gov (United States)

Melching, Charles S.; Chang, T.J.

1996-01-01

Water-quality processes in the Salt Creek watershed in northeastern Illinois were simulated with a computer model. Selected waste-load scenarios for 7-day, 10-year low-flow conditions were simulated in the stream system. The model development involved the calibration of the U.S. Environmental Protection Agency QUAL2E model to water-quality constituent concentration data collected by the Illinois Environmental Protection Agency (IEPA) for a diel survey on August 29-30, 1995, and the verification of this model with water-quality constituent concentration data collected by the IEPA for a diel survey on June 27-28, 1995. In-stream measurements of sediment oxygen demand rates and carbonaceous biochemical oxygen demand (CBOD) decay rates by the IEPA and traveltime and reaeration-rate coefficients by the U.S. Geological Survey facilitated the development of a model for simulation of water quality in the Salt Creek watershed. In general, the verification of the calibrated model increased confidence in the utility of the model for water-quality planning in the Salt Creek watershed. However, the model was adjusted to better simulate constituent concentrations measured during the June 27-28, 1995, diel survey. Two versions of the QUAL2E model were utilized to simulate dissolved oxygen (DO) concentrations in the Salt Creek watershed for selected effluent discharge and concentration scenarios for water-quality planning: (1) the QUAL2E model calibrated to the August 29-30, 1995, diel survey, and (2) the QUAL2E model adjusted to the June 27-28, 1995, diel survey. The results of these simulations indicated that the QUAL2E model adjusted to the June 27-28, 1995, diel survey simulates reliable information for water-quality planning. The results of these simulations also indicated that to maintain DO concentrations greater than 5 milligrams per liter (mg/L) throughout most of Salt Creek for 7-day, 10-year low-flow conditions, the sewage-treatment plants (STP's) must discharge

Applications of continuous water quality monitoring techniques for more efficient water quality research and water resources management

NARCIS (Netherlands)

Rozemeijer, J.C.; Velde, Y. van der; Broers, H.P.; Geer, F. van

2013-01-01

Understanding and taking account of dynamics in water quality is essential for adequate water quality policy and management. In conventional regional surface water and upper groundwater quality monitoring, measurement frequencies are too low to capture the short-term dynamic behavior of solute

Water Quality Assessment for Deep-water Channel area of Guangzhou Port based on the Comprehensive Water Quality Identification Index Method

Science.gov (United States)

Chen, Yi

2018-03-01

The comprehensive water quality identification index method is able to assess the general water quality situation comprehensively and represent the water quality classification; water environment functional zone achieves pollution level and standard objectively and systematically. This paper selects 3 representative zones along deep-water channel of Guangzhou port and applies comprehensive water quality identification index method to calculate sea water quality monitoring data for different selected zones from year 2006 to 2014, in order to investigate the temporal variation of water quality along deep-water channel of Guangzhou port. The comprehensive water quality level from north to south presents an increased trend, and the water quality of the three zones in 2014 is much better than in 2006. This paper puts forward environmental protection measurements and suggestions for Pearl River Estuary, provides data support and theoretical basis for studied sea area pollution prevention and control.

Land use change and conversion effects on ground water quality trends: An integration of land change modeler in GIS and a new Ground Water Quality Index developed by fuzzy multi-criteria group decision-making models.

Science.gov (United States)

Shooshtarian, Mohammad Reza; Dehghani, Mansooreh; Margherita, Ferrante; Gea, Oliveri Conti; Mortezazadeh, Shima

2018-04-01

This study aggregated Land Change Modeller (LCM) as a useful model in GIS with an extended Groundwater Quality Index (GWQI) developed by fuzzy Multi-Criteria Group Decision-Making models to investigate the effect of land use change and conversion on groundwater quality being supplied for drinking. The model's performance was examined through an applied study in Shiraz, Iran, in a five year period (2011 to 2015). Four land use maps including urban, industrial, garden, and bare were employed in LCM model and the impact of change in area and their conversion to each other on GWQI changes was analysed. The correlation analysis indicated that increase in the urban land use area and conversion of bare to the residential/industrial land uses, had a relation with water quality decrease. Integration of LCM and GWQI can accurately and logically provide a numerical analysis of the possible impact of land use change and conversion, as one of the influencing factors, on the groundwater quality. Hence, the methodology could be used in urban development planning and management in macro level. Copyright © 2018. Published by Elsevier Ltd.

An innovative modeling approach using Qual2K and HEC-RAS integration to assess the impact of tidal effect on River Water quality simulation.

Science.gov (United States)

Fan, Chihhao; Ko, Chun-Han; Wang, Wei-Shen

2009-04-01

Water quality modeling has been shown to be a useful tool in strategic water quality management. The present study combines the Qual2K model with the HEC-RAS model to assess the water quality of a tidal river in northern Taiwan. The contaminant loadings of biochemical oxygen demand (BOD), ammonia nitrogen (NH(3)-N), total phosphorus (TP), and sediment oxygen demand (SOD) are utilized in the Qual2K simulation. The HEC-RAS model is used to: (i) estimate the hydraulic constants for atmospheric re-aeration constant calculation; and (ii) calculate the water level profile variation to account for concentration changes as a result of tidal effect. The results show that HEC-RAS-assisted Qual2K simulations taking tidal effect into consideration produce water quality indices that, in general, agree with the monitoring data of the river. Comparisons of simulations with different combinations of contaminant loadings demonstrate that BOD is the most import contaminant. Streeter-Phelps simulation (in combination with HEC-RAS) is also performed for comparison, and the results show excellent agreement with the observed data. This paper is the first report of the innovative use of a combination of the HEC-RAS model and the Qual2K model (or Streeter-Phelps equation) to simulate water quality in a tidal river. The combination is shown to provide an alternative for water quality simulation of a tidal river when available dynamic-monitoring data are insufficient to assess the tidal effect of the river.

The role of headwater streams in downstream water quality

Science.gov (United States)

Alexander, R.B.; Boyer, E.W.; Smith, R.A.; Schwarz, G.E.; Moore, R.B.

2007-01-01

Knowledge of headwater influences on the water-quality and flow conditions of downstream waters is essential to water-resource management at all governmental levels; this includes recent court decisions on the jurisdiction of the Federal Clean Water Act (CWA) over upland areas that contribute to larger downstream water bodies. We review current watershed research and use a water-quality model to investigate headwater influences on downstream receiving waters. Our evaluations demonstrate the intrinsic connections of headwaters to landscape processes and downstream waters through their influence on the supply, transport, and fate of water and solutes in watersheds. Hydrological processes in headwater catchments control the recharge of subsurface water stores, flow paths, and residence times of water throughout landscapes. The dynamic coupling of hydrological and biogeochemical processes in upland streams further controls the chemical form, timing, and longitudinal distances of solute transport to downstream waters. We apply the spatially explicit, mass-balance watershed model SPARROW to consider transport and transformations of water and nutrients throughout stream networks in the northeastern United States. We simulate fluxes of nitrogen, a primary nutrient that is a water-quality concern for acidification of streams and lakes and eutrophication of coastal waters, and refine the model structure to include literature observations of nitrogen removal in streams and lakes. We quantify nitrogen transport from headwaters to downstream navigable waters, where headwaters are defined within the model as first-order, perennial streams that include flow and nitrogen contributions from smaller, intermittent and ephemeral streams. We find that first-order headwaters contribute approximately 70% of the mean-annual water volume and 65% of the nitrogen flux in second-order streams. Their contributions to mean water volume and nitrogen flux decline only marginally to about 55% and

Inverse modeling with RZWQM2 to predict water quality

Science.gov (United States)

Nolan, Bernard T.; Malone, Robert W.; Ma, Liwang; Green, Christopher T.; Fienen, Michael N.; Jaynes, Dan B.

2011-01-01

This chapter presents guidelines for autocalibration of the Root Zone Water Quality Model (RZWQM2) by inverse modeling using PEST parameter estimation software (Doherty, 2010). Two sites with diverse climate and management were considered for simulation of N losses by leaching and in drain flow: an almond [Prunus dulcis (Mill.) D.A. Webb] orchard in the San Joaquin Valley, California and the Walnut Creek watershed in central Iowa, which is predominantly in corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] rotation. Inverse modeling provides an objective statistical basis for calibration that involves simultaneous adjustment of model parameters and yields parameter confidence intervals and sensitivities. We describe operation of PEST in both parameter estimation and predictive analysis modes. The goal of parameter estimation is to identify a unique set of parameters that minimize a weighted least squares objective function, and the goal of predictive analysis is to construct a nonlinear confidence interval for a prediction of interest by finding a set of parameters that maximizes or minimizes the prediction while maintaining the model in a calibrated state. We also describe PEST utilities (PAR2PAR, TSPROC) for maintaining ordered relations among model parameters (e.g., soil root growth factor) and for post-processing of RZWQM2 outputs representing different cropping practices at the Iowa site. Inverse modeling provided reasonable fits to observed water and N fluxes and directly benefitted the modeling through: (i) simultaneous adjustment of multiple parameters versus one-at-a-time adjustment in manual approaches; (ii) clear indication by convergence criteria of when calibration is complete; (iii) straightforward detection of nonunique and insensitive parameters, which can affect the stability of PEST and RZWQM2; and (iv) generation of confidence intervals for uncertainty analysis of parameters and model predictions. Composite scaled sensitivities, which

Water quality assessment with hierarchical cluster analysis based on Mahalanobis distance.

Science.gov (United States)

Du, Xiangjun; Shao, Fengjing; Wu, Shunyao; Zhang, Hanlin; Xu, Si

2017-07-01

Water quality assessment is crucial for assessment of marine eutrophication, prediction of harmful algal blooms, and environment protection. Previous studies have developed many numeric modeling methods and data driven approaches for water quality assessment. The cluster analysis, an approach widely used for grouping data, has also been employed. However, there are complex correlations between water quality variables, which play important roles in water quality assessment but have always been overlooked. In this paper, we analyze correlations between water quality variables and propose an alternative method for water quality assessment with hierarchical cluster analysis based on Mahalanobis distance. Further, we cluster water quality data collected form coastal water of Bohai Sea and North Yellow Sea of China, and apply clustering results to evaluate its water quality. To evaluate the validity, we also cluster the water quality data with cluster analysis based on Euclidean distance, which are widely adopted by previous studies. The results show that our method is more suitable for water quality assessment with many correlated water quality variables. To our knowledge, it is the first attempt to apply Mahalanobis distance for coastal water quality assessment.

What's in Your Water? An Educator's Guide to Water Quality.

Science.gov (United States)

Constabile, Kerry, Comp.; Craig, Heidi, Comp.; O'Laughlin, Laura, Comp.; Reiss, Anne Bei, Comp.; Spencer, Liz, Comp.

This guide provides basic information on the Clean Water Act, watersheds, and testing for water quality, and presents four science lesson plans on water quality. Activities include: (1) "Introduction to Water Quality"; (2) "Chemical Water Quality Testing"; (3) "Biological Water Quality Testing"; and (4) "What Can We Do?" (YDS)

Control options for river water quality improvement: a case study of ...

African Journals Online (AJOL)

Using a simple conceptual dynamic river water quality model, the effects of different basin-wide water quality management options on downstream water quality improvements in a semi-arid river, the Crocodile River (South Africa) were investigated. When a river is impacted by high rates of freshwater withdrawal (in its ...

Assessment of water quality

International Nuclear Information System (INIS)

Qureshi, I.H.

2002-01-01

Water is the most essential component of all living things and it supports the life process. Without water, it would not have been possible to sustain life on this planet. The total quantity of water on earth is estimated to be 1.4 trillion cubic meter. Of this, less than 1 % water, present in rivers and ground resources is available to meet our requirement. These resources are being contaminated with toxic substances due to ever increasing environmental pollution. To reduce this contamination, many countries have established standards for the discharge of municipal and industrial waste into water streams. We use water for various purposes and for each purpose we require water of appropriate quality. The quality of water is assessed by evaluating the physical chemical, biological and radiological characteristics of water. Water for drinking and food preparation must be free from turbidity, colour, odour and objectionable tastes, as well as from disease causing organisms and inorganic and organic substances, which may produce adverse physiological effects, Such water is referred to as potable water and is produced by treatment of raw water, involving various unit operations. The effectiveness of the treatment processes is checked by assessing the various parameters of water quality, which involves sampling and analysis of water and comparison with the National Quality Standards or WHO standards. Water which conforms to these standards is considered safe and palatable for human consumption. Periodic assessment of water is necessary, to ensure the quality of water supplied to the public. This requires proper sampling at specified locations and analysis of water, employing reliable analytical techniques. (author)

Modeling of the quality of water of River Tula, state of Hidalgo, Mexico

International Nuclear Information System (INIS)

Montelongo Casanova, Rosalba; Gordillo Martinez, Alberto Jose; Otazo Sanchez, Elena Maria; Villagomez Ibarra, Jose Roberto; Acevedo Sandoval, Otilio Arturo; Prieto Garcia, Francisco

2008-01-01

The central objective of this work is to model the quality of the water of Tula River, from the central emitter to their confluence with the Endho Dam. It was evaluated during two years, considering a length of 50 km in 4 zones and 35 sites of sampling. The central emitter contributes to the greater amount of organic matter, water without treatment of the city of Mexico and co urbane zone. The values of DBO varied from 1.16 up to 486.81 mg O 2 /L; the oxygen dissolved between 1.52 and 5.82 mg/L. This implies affectation for the development of the aquatic life. The alkalinity exceeded the ecological criteria of quality as a source of potable water with value of 458.01 mg. the fats displayed variations from 0.9 mg/l up to 18.1 mg/l and ammoniacal nitrogen outside the limits established for protection of the aquatic life with values from 0.09 a 64 mg/L; nitrates (6.24 mg/L) and nitrites (0.5-1.304 mg/L) exceed the ecological criteria. The metals cadmium, lead, iron, manganese and zinc are in concentrations over the permissible rank and in some sections mercury presence was reported. The fecal coliforms were detected in values from 2.1x10 4 up to 2.40x10 1 1 NMP/100 milliliters. In general, the toxicity in the residual water unloading demonstrated that all appears of moderate to high. Only there were three monitored stations (19%) with excellent quality, 3 smaller or equal DBOs to mg/L, which is considered like water no contaminated by biodegradable organic matter

[Water environmental capacity calculation model for the rivers in drinking water source conservation area].

Science.gov (United States)

Chen, Ding-jiang; Lü, Jun; Shen, Ye-na; Jin, Shu-quan; Shi, Yi-ming

2008-09-01

Based on the one-dimension model for water environmental capacity (WEC) in river, a new model for the WEC estimation in river-reservoir system was developed in drinking water source conservation area (DWSCA). In the new model, the concept was introduced that the water quality target of the rivers in DWSCA was determined by the water quality demand of reservoir for drinking water source. It implied that the WEC of the reservoir could be used as the water quality control target at the reach-end of the upstream rivers in DWSCA so that the problems for WEC estimation might be avoided that the differences of the standards for a water quality control target between in river and in reservoir, such as the criterions differences for total phosphorus (TP)/total nitrogen (TN) between in reservoir and in river according to the National Surface Water Quality Standard of China (GB 3838-2002), and the difference of designed hydrology conditions for WEC estimation between in reservoir and in river. The new model described the quantitative relationship between the WEC of drinking water source and of the river, and it factually expressed the continuity and interplay of these low water areas. As a case study, WEC for the rivers in DWSCA of Laohutan reservoir located in southeast China was estimated using the new model. Results indicated that the WEC for TN and TP was 65.05 t x a(-1) and 5.05 t x a(-1) in the rivers of the DWSCA, respectively. According to the WEC of Laohutan reservoir and current TN and TP quantity that entered into the rivers, about 33.86 t x a(-1) of current TN quantity should be reduced in the DWSCA, while there was 2.23 t x a(-1) of residual WEC of TP in the rivers. The modeling method was also widely applicable for the continuous water bodies with different water quality targets, especially for the situation of higher water quality control target in downstream water body than that in upstream.

Accelerate Water Quality Improvement

Science.gov (United States)

EPA is committed to accelerating water quality improvement and minimizing negative impacts to aquatic life from contaminants and other stressors in the Bay Delta Estuary by working with California Water Boards to strengthen water quality improvement plans.

Long-term integrated river basin planning and management of water quantity and water quality in mining impacted catchments

Science.gov (United States)

Pohle, Ina; Zimmermann, Kai; Claus, Thomas; Koch, Hagen; Gädeke, Anne; Uhlmann, Wilfried; Kaltofen, Michael; Müller, Fabian; Redetzky, Michael; Schramm, Martina; Schoenheinz, Dagmar; Grünewald, Uwe

2015-04-01

During the last decades, socioeconomic change in the catchment of the Spree River, a tributary of the Elbe, has been to a large extent associated with lignite mining activities and the rapid decrease of these activities in the 1990s. There are multiple interconnections between lignite mining and water management both in terms of water quantity and quality. During the active mining period a large-scale groundwater depression cone has been formed while river discharges have been artificially increased. Now, the decommissioned opencast mines are being transformed into Europe's largest man-made lake district. However, acid mine drainage causes low pH in post mining lakes and high concentrations of iron and sulphate in post mining lakes and the river system. Next to potential changes in mining activities, also the potential impacts of climate change (increasing temperature and decreasing precipitation) on water resources of the region are of major interest. The fundamental question is to what extent problems in terms of water quantity and water quality are exacerbated and whether they can be mitigated by adaptation measures. In consequence, long term water resource planning in the region has to formulate adaptation measures to climate change and socioeconomic change in terms of mining activities which consider both, water quantity and water quality aspects. To assess potential impacts of climate and socioeconomic change on water quantity and water quality of the Spree River catchment up to the Spremberg reservoir in the scenario period up to 2052, we used a model chain which consists of (i) the regional climate model STAR (scenarios with a further increase in temperature of 0 and 2 K), (ii) mining scenarios (mining discharges, cooling water consumption of thermal power plants), (iii) the ecohydrological model SWIM (natural water balance), (iv) the long term water management model WBalMo (managed discharges, withdrawal of water users, reservoir operation) and (v) the

STUDY OF POND WATER QUALITY BY THE ASSESSMENT OF PHYSICOCHEMICAL PARAMETERS AND WATER QUALITY INDEX

OpenAIRE

Vinod Jena; Satish Dixit; Ravi ShrivastavaSapana Gupta; Sapana Gupta

2013-01-01

Water quality index (WQI) is a dimensionless number that combines multiple water quality factors into a single number by normalizing values to subjective rating curves. Conventionally it has been used for evaluating the quality of water for water resources suchas rivers, streams and lakes, etc. The present work is aimed at assessing the Water Quality Index (W.Q.I) ofpond water and the impact of human activities on it. Physicochemical parameters were monitored for the calculation of W.Q.I for ...

Water Quality Monitoring

Science.gov (United States)

2002-01-01

With the backing of NASA, researchers at Michigan State University, the University of Minnesota, and the University of Wisconsin have begun using satellite data to measure lake water quality and clarity of the lakes in the Upper Midwest. This false color IKONOS image displays the water clarity of the lakes in Eagan, Minnesota. Scientists measure the lake quality in satellite data by observing the ratio of blue to red light in the satellite data. When the amount of blue light reflecting off of the lake is high and the red light is low, a lake generally had high water quality. Lakes loaded with algae and sediments, on the other hand, reflect less blue light and more red light. In this image, scientists used false coloring to depict the level of clarity of the water. Clear lakes are blue, moderately clear lakes are green and yellow, and murky lakes are orange and red. Using images such as these along with data from the Landsat satellites and NASA's Terra satellite, the scientists plan to create a comprehensive water quality map for the entire Great Lakes region in the next few years. For more information, read: Testing the Waters (Image courtesy Upper Great Lakes Regional Earth Science Applications Center, based on data copyright Space Imaging)

Water Quality of Hills Water, Supply Water and RO Water Machine at Ulu Yam Selangor

Science.gov (United States)

Ngadiman, N.; ‘I Bahari, N.; Kaamin, M.; Hamid, N. B.; Mokhtar, M.; Sahat, S.

2016-07-01

The rapid development resulted in the deterioration of the quality of drinking water in Malaysia. Recognizing the importance of water quality, new alternatives for drinking water such as mineral water processing from reverse osmosis (RO) machine become more popular. Hence, the demand for mineral water, natural spring water or water from the hills or mountains rose lately. More consumers believed the quality of these spring water better than other source of drinking water. However, the quality of all the drinking water sources is to meet the required quality standard. Therefore, this paper aims to measure the quality of the waters from hills, from RO machine and the water supply in Ulu Yam, Selangor Batang Kali, Malaysia. The water quality was determined based on following parameters: ammoniacal nitrogen (NH3), iron (Fe), turbidity (NTU) and pH. The results show that the water from hills has better quality compared to water supply and water from RO machine. The value of NH3 ranged from 0.03 mg/L- 0.67 mg/L; Fe was from 0.03mg/L - 0.12 mg/L, turbidity at 0.42 NTU - 0.88 NTU and pH is at 6.60 - 0.71. Based on the studied parameters, all three types of water are fit for drinking and have met the required national drinking water quality standard.

Hourly Water Quality Dynamics in Rivers Downstream of Urban Areas: Quantifying Seasonal Variation and Modelling Impacts of Urban Growth

Science.gov (United States)

Hutchins, M.; McGrane, S. J.; Miller, J. D.; Hitt, O.; Bowes, M.

2016-12-01

Continuous monitoring of water flows and quality is invaluable in improving understanding of the influence of urban areas on river health. When used to inform predictive modelling, insights can be gained as to how urban growth may affect the chemical and biological quality of rivers as they flow downstream into larger waterbodies. Water flow and quality monitoring in two urbanising sub-catchments (long term flow records are available, but particular focus is given to monitoring of an extended set of sites during prolonged winter rainfall. In the Ray sub-catchment streams were monitored in which urban cover varied across a range of 7-78%. A rural-urban gradient in DO was apparent in the low flow period prior to the storms. Transient low DO (works (STW). In this respect temperature- and respiration-driven DO sags in summer were at least if not more severe than those driven by the winter storms. Likewise, although winter storm NH4 concentrations violated EU legislation downstream of the STW, they were lower than summer concentrations in pollutant flushes following dry spells. In contrast the predominant phenomenon affecting water quality in the Cut during the storms was dilution. Here, a river water quality model was calibrated and applied over the course of a year to capture the importance of periphyton photosynthesis and respiration cycles in determining water quality and to predict the influence of hypothetical urban growth on downstream river health. The periods monitored intensively, dry spells followed by prolonged rainfall, represent: (i) marked changes in conditions likely to become more prevalent in future, (ii) situations under which water quality in urban areas is likely to be particularly vulnerable, being influenced for example by first flush effects followed by capacity exceedance at STW. Despite this, whilst being somewhat long lasting in places, impacts on DO were not severe.

Sediment delivery estimates in water quality models altered by resolution and source of topographic data.

Science.gov (United States)

Beeson, Peter C; Sadeghi, Ali M; Lang, Megan W; Tomer, Mark D; Daughtry, Craig S T

2014-01-01

Moderate-resolution (30-m) digital elevation models (DEMs) are normally used to estimate slope for the parameterization of non-point source, process-based water quality models. These models, such as the Soil and Water Assessment Tool (SWAT), use the Universal Soil Loss Equation (USLE) and Modified USLE to estimate sediment loss. The slope length and steepness factor, a critical parameter in USLE, significantly affects sediment loss estimates. Depending on slope range, a twofold difference in slope estimation potentially results in as little as 50% change or as much as 250% change in the LS factor and subsequent sediment estimation. Recently, the availability of much finer-resolution (∼3 m) DEMs derived from Light Detection and Ranging (LiDAR) data has increased. However, the use of these data may not always be appropriate because slope values derived from fine spatial resolution DEMs are usually significantly higher than slopes derived from coarser DEMs. This increased slope results in considerable variability in modeled sediment output. This paper addresses the implications of parameterizing models using slope values calculated from DEMs with different spatial resolutions (90, 30, 10, and 3 m) and sources. Overall, we observed over a 2.5-fold increase in slope when using a 3-m instead of a 90-m DEM, which increased modeled soil loss using the USLE calculation by 130%. Care should be taken when using LiDAR-derived DEMs to parameterize water quality models because doing so can result in significantly higher slopes, which considerably alter modeled sediment loss. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Progress and lessons learned from water-quality monitoring networks

Science.gov (United States)

Myers, Donna N.; Ludtke, Amy S.

2017-01-01

Stream-quality monitoring networks in the United States were initiated and expanded after passage of successive federal water-pollution control laws from 1948 to 1972. The first networks addressed information gaps on the extent and severity of stream pollution and served as early warning systems for spills. From 1965 to 1972, monitoring networks expanded to evaluate compliance with stream standards, track emerging issues, and assess water-quality status and trends. After 1972, concerns arose regarding the ability of monitoring networks to determine if water quality was getting better or worse and why. As a result, monitoring networks adopted a hydrologic systems approach targeted to key water-quality issues, accounted for human and natural factors affecting water quality, innovated new statistical methods, and introduced geographic information systems and models that predict water quality at unmeasured locations. Despite improvements, national-scale monitoring networks have declined over time. Only about 1%, or 217, of more than 36,000 US Geological Survey monitoring sites sampled from 1975 to 2014 have been operated throughout the four decades since passage of the 1972 Clean Water Act. Efforts to sustain monitoring networks are important because these networks have collected information crucial to the description of water-quality trends over time and are providing information against which to evaluate future trends.

Application of a water quality model for determining instream aeration station location and operational rules: A case study

Directory of Open Access Journals (Sweden)

Charles S. Melching

2018-01-01

Full Text Available Instream aeration has been used as a supplement to secondary treatment or a substitute for tertiary treatment for meeting dissolved oxygen (DO standards in rivers. Many studies have used water quality models to determine the number, location, and capacity of instream aeration stations (IASs needed to meet DO standards in combination with other pollution control measures. DO concentrations have been improved in the North Shore Channel and North Branch Chicago River by the Devon Avenue IAS for more than 35 years. A study was initiated to determine whether it was better to rehabilitate or relocate this station and to determine appropriate operational guidance for the IAS at the selected location. A water quality model capable of simulating DO concentrations during unsteady flow was used to evaluate the proper location for an IAS and operational guidance for this IAS. Three test years, a dry year, a wet year, and an extreme year, were considered in the evaluation. The study found that the Devon Avenue IAS should be rehabilitated as this location performed as well as or better than any of 10 alternative locations. According to the new operational guidance for this IAS, the amount of time with blowers operating could be substantially reduced compared to traditional operations while at the same time the attainment of the DO standards could be increased. This study shows that a carefully designed modeling study is key to effective selection, location, and operation of IASs such that attainment of DO standards can be maximized while operation hours of blowers can be minimized. Keywords: Instream aeration, Dissolved oxygen, Water quality modeling, Water quality management, Computer simulation

43 CFR 414.5 - Water quality.

Science.gov (United States)

2010-10-01

... 43 Public Lands: Interior 1 2010-10-01 2010-10-01 false Water quality. 414.5 Section 414.5 Public... APPORTIONMENT IN THE LOWER DIVISION STATES Water Quality and Environmental Compliance § 414.5 Water quality. (a) Water Quality is not guaranteed. The Secretary does not warrant the quality of water released or...

Evaluating the APEX model for simulating streamflow and water quality on ten agricultural watersheds in the U.S.

Science.gov (United States)

Simulation models are increasingly used to assess water quality constituent losses from agricultural systems. Mis-use often gives irrelevant or erroneous answers. The Agricultural Policy Environmental Extender (APEX) model is emerging as one of the premier modeling tools for fields, farms, and agr...

Quality-control design for surface-water sampling in the National Water-Quality Network

Science.gov (United States)

Riskin, Melissa L.; Reutter, David C.; Martin, Jeffrey D.; Mueller, David K.

2018-04-10

The data-quality objectives for samples collected at surface-water sites in the National Water-Quality Network include estimating the extent to which contamination, matrix effects, and measurement variability affect interpretation of environmental conditions. Quality-control samples provide insight into how well the samples collected at surface-water sites represent the true environmental conditions. Quality-control samples used in this program include field blanks, replicates, and field matrix spikes. This report describes the design for collection of these quality-control samples and the data management needed to properly identify these samples in the U.S. Geological Survey’s national database.

Is water age a reliable indicator for evaluating water quality effectiveness of water diversion projects in eutrophic lakes?

Science.gov (United States)

Zhang, Xiaoling; Zou, Rui; Wang, Yilin; Liu, Yong; Zhao, Lei; Zhu, Xiang; Guo, Huaicheng

2016-11-01

Water diversion has been applied increasingly to promote the exchange of lake water and to control eutrophication of lakes. The accelerated water exchange and mass transport by water diversion can usually be represented by water age. But the responses of water quality after water diversion is still disputed. The reliability of using water age for evaluating the effectiveness of water diversion projects in eutrophic lakes should be thereby explored further. Lake Dianchi, a semi-closed plateau lake in China, has suffered severe eutrophication since the 1980s, and it is one of the three most eutrophic lakes in China. There was no significant improvement in water quality after an investment of approximately 7.7 billion USD and numerous project efforts from 1996 to 2015. After the approval of the Chinese State Council, water has been transferred to Lake Dianchi to alleviate eutrophication since December 2013. A three-dimensional hydrodynamic and water quality model and eight scenarios were developed in this study to quantity the influence of this water diversion project on water quality in Lake Dianchi. The model results showed that (a) Water quality (TP, TN, and Chla) could be improved by 13.5-32.2%, much lower than the approximate 50% reduction in water age; (b) Water exchange had a strong positive relationship with mean TP, and mean Chla had exactly the same response to water diversion as mean TN; (c) Water level was more beneficial for improving hydrodynamic and nutrient concentrations than variation in the diverted inflowing water volume; (d) The water diversion scenario of doubling the diverted inflow rate in the wet season with the water level of 1886.5 m and 1887 m in the remaining months was the best water diversion mode for mean hydrodynamics and TP, but the scenario of doubling the diverted inflow rate in the wet season with 1887 m throughout the year was optimum for mean TN and Chla; (e) Water age influenced the effectiveness of water diversion on the

Water quality management of aquifer recharge using advanced tools.

Science.gov (United States)

Lazarova, Valentina; Emsellem, Yves; Paille, Julie; Glucina, Karl; Gislette, Philippe

2011-01-01

Managed aquifer recharge (MAR) with recycled water or other alternative resources is one of the most rapidly growing techniques that is viewed as a necessity in water-short areas. In order to better control health and environmental effects of MAR, this paper presents two case studies demonstrating how to improve water quality, enable reliable tracing of injected water and better control and manage MAR operation in the case of indirect and direct aquifer recharge. Two water quality management strategies are illustrated on two full-scale case studies, including the results of the combination of non conventional and advanced technologies for water quality improvement, comprehensive sampling and monitoring programs including emerging pollutants, tracer studies using boron isotopes and integrative aquifer 3D GIS hydraulic and hydrodispersive modelling.

Solid Waste and Water Quality Management Models for Sagarmatha National Park and Buffer Zone, Nepal.

NARCIS (Netherlands)

Manfredi, Emanuela Chiara; Flury, Bastian; Viviano, Gaetano; Thakuri, Sudeep; Khanal, Sanjay Nath; Jha, Pramod Kumar; Maskey, Ramesh Kumar; Kayastha, Rijan Bhakta; Kafle, Kumud Raj; Bhochhibhoya, Silu; Ghimire, Narayan Prasad; Shrestha, Bharat Babu; Chaudhary, Gyanendra; Giannino, Francesco; Carteni, Fabrizio; Mazzoleni, Stefano; Salerno, Franco

2010-01-01

The problem of supporting decision- and policy-makers in managing issues related to solid waste and water quality was addressed within the context of a participatory modeling framework in the Sagarmatha National Park and Buffer Zone in Nepal. We present the main findings of management-oriented

Setting water quality criteria for agricultural water reuse purposes

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K. Müller

2017-06-01

Full Text Available The use of reclaimed water for agricultural irrigation is practiced worldwide and will increase in the future. The definition of water quality limits is a useful instrument for the assessment of water quality regarding its suitability for irrigation purposes and the performance of wastewater treatment steps. This study elaborates water quality objectives for a water reuse project in a setting where national guidelines do not exist. Internationally established guidelines are therefore applied to the local context. Additional limits for turbidity, total suspended solids, biochemical and chemical oxygen demand, total phosphorus and potassium are suggested to meet the requirements of water reuse projects. Emphasis is put on water quality requirements prior to UV disinfection and nutrient requirements of cultivated crops. The presented values can be of assistance when monitoring reclaimed water quality. To facilitate the realization of water reuse projects, comprehensive and more detailed information, in particular on water quality requirements prior to disinfection steps, should be provided as well as regarding the protection of the irrigation infrastructure.

Using QMRAcatch - a stochastic hydrological water quality and infection risk model - to identify sustainable management options for long term drinking water resource planning

Science.gov (United States)

Derx, J.; Demeter, K.; Schijven, J. F.; Sommer, R.; Zoufal-Hruza, C. M.; Kromp, H.; Farnleitner, A.; Blaschke, A. P.

2017-12-01

River water resources in urban environments play a critical role in sustaining human health and ecosystem services, as they are used for drinking water production, bathing and irrigation. In this study the hydrological water quality model QMRAcatch was used combined with measured concentrations of human enterovirus and human-associated genetic fecal markers. The study area is located at a river/floodplain area along the Danube which is used for drinking water production by river bank filtration and further disinfection. QMRAcatch was previously developed to support long term planning of water resources in accordance with a public infection protection target (Schijven et al., 2015). Derx et al. 2016 previously used QMRAcatch for evaluating the microbiological quality and required virus-reduction targets at the study area for the current and robust future "crisis" scenarios, i.e. for the complete failure of wastewater treatment plants and infection outbreaks. In contrast, the aim of this study was to elaborate future scenarios based on projected climate and population changes in collaboration with urban water managers. The identified scenarios until 2050 include increased wastewater discharge rates due to the projected urban population growth and more frequent storm and overflow events of urban sewer systems following forecasted changes in climate and hydrology. Based on the simulation results for the developed scenarios sustainable requirements of the drinking water treatment system for virus reductions were re-evaluated to achieve the health risk target. The model outcomes are used to guide practical and scientifically sound management options for long term water resource planning. This paper was supported by FWF (Vienna Doctoral Program on Water Resource Systems W1219-N22) and the GWRS project (Vienna Water) as part of the "(New) Danube-Lower Lobau Network Project" funded by the Government of Austria and Vienna, and the European Agricultural Fund for Rural

Multivariate Bias Correction Procedures for Improving Water Quality Predictions from the SWAT Model

Science.gov (United States)

Arumugam, S.; Libera, D.

2017-12-01

Water quality observations are usually not available on a continuous basis for longer than 1-2 years at a time over a decadal period given the labor requirements making calibrating and validating mechanistic models difficult. Further, any physical model predictions inherently have bias (i.e., under/over estimation) and require post-simulation techniques to preserve the long-term mean monthly attributes. This study suggests a multivariate bias-correction technique and compares to a common technique in improving the performance of the SWAT model in predicting daily streamflow and TN loads across the southeast based on split-sample validation. The approach is a dimension reduction technique, canonical correlation analysis (CCA) that regresses the observed multivariate attributes with the SWAT model simulated values. The common approach is a regression based technique that uses an ordinary least squares regression to adjust model values. The observed cross-correlation between loadings and streamflow is better preserved when using canonical correlation while simultaneously reducing individual biases. Additionally, canonical correlation analysis does a better job in preserving the observed joint likelihood of observed streamflow and loadings. These procedures were applied to 3 watersheds chosen from the Water Quality Network in the Southeast Region; specifically, watersheds with sufficiently large drainage areas and number of observed data points. The performance of these two approaches are compared for the observed period and over a multi-decadal period using loading estimates from the USGS LOADEST model. Lastly, the CCA technique is applied in a forecasting sense by using 1-month ahead forecasts of P & T from ECHAM4.5 as forcings in the SWAT model. Skill in using the SWAT model for forecasting loadings and streamflow at the monthly and seasonal timescale is also discussed.

Model documentation for relations between continuous real-time and discrete water-quality constituents in Cheney Reservoir near Cheney, Kansas, 2001--2009

Science.gov (United States)

Stone, Mandy L.; Graham, Jennifer L.; Gatotho, Jackline W.

2013-01-01

Cheney Reservoir, located in south-central Kansas, is one of the primary water supplies for the city of Wichita, Kansas. The U.S. Geological Survey has operated a continuous real-time water-quality monitoring station in Cheney Reservoir since 2001; continuously measured physicochemical properties include specific conductance, pH, water temperature, dissolved oxygen, turbidity, fluorescence (wavelength range 650 to 700 nanometers; estimate of total chlorophyll), and reservoir elevation. Discrete water-quality samples were collected during 2001 through 2009 and analyzed for sediment, nutrients, taste-and-odor compounds, cyanotoxins, phytoplankton community composition, actinomycetes bacteria, and other water-quality measures. Regression models were developed to establish relations between discretely sampled constituent concentrations and continuously measured physicochemical properties to compute concentrations of constituents that are not easily measured in real time. The water-quality information in this report is important to the city of Wichita because it allows quantification and characterization of potential constituents of concern in Cheney Reservoir. This report updates linear regression models published in 2006 that were based on data collected during 2001 through 2003. The update uses discrete and continuous data collected during May 2001 through December 2009. Updated models to compute dissolved solids, sodium, chloride, and suspended solids were similar to previously published models. However, several other updated models changed substantially from previously published models. In addition to updating relations that were previously developed, models also were developed for four new constituents, including magnesium, dissolved phosphorus, actinomycetes bacteria, and the cyanotoxin microcystin. In addition, a conversion factor of 0.74 was established to convert the Yellow Springs Instruments (YSI) model 6026 turbidity sensor measurements to the newer YSI

Quality-assurance plan for water-quality activities in the U.S. Geological Survey Washington Water Science Center

Science.gov (United States)

Conn, Kathleen E.; Huffman, Raegan L.; Barton, Cynthia

2017-05-08

In accordance with guidelines set forth by the Office of Water Quality in the Water Mission Area of the U.S. Geological Survey, a quality-assurance plan has been created for use by the Washington Water Science Center (WAWSC) in conducting water-quality activities. This qualityassurance plan documents the standards, policies, and procedures used by the WAWSC for activities related to the collection, processing, storage, analysis, and publication of water-quality data. The policies and procedures documented in this quality-assurance plan for water-quality activities complement the quality-assurance plans for surface-water and groundwater activities at the WAWSC.

Water Quality Is a Poor Predictor of Recreational Hotspots in England.

Directory of Open Access Journals (Sweden)

Guy Ziv

Full Text Available Maintaining and improving water quality is key to the protection and restoration of aquatic ecosystems, which provide important benefits to society. In Europe, the Water Framework Directive (WFD defines water quality based on a set of biological, hydro-morphological and chemical targets, and aims to reach good quality conditions in all river bodies by the year 2027. While recently it has been argued that achieving these goals will deliver and enhance ecosystem services, in particular recreational services, there is little empirical evidence demonstrating so. Here we test the hypothesis that good water quality is associated with increased utilization of recreational services, combining four surveys covering walking, boating, fishing and swimming visits, together with water quality data for all water bodies in eight River Basin Districts (RBDs in England. We compared the percentage of visits in areas of good water quality to a set of null models accounting for population density, income, age distribution, travel distance, public access, and substitutability. We expect such association to be positive, at least for fishing (which relies on fish stocks and swimming (with direct contact to water. We also test if these services have stronger association with water quality relative to boating and walking alongside rivers, canals or lakeshores. In only two of eight RBDs (Northumbria and Anglian were both criteria met (positive association, strongest for fishing and swimming when comparing to at least one of the null models. This conclusion is robust to variations in dataset size. Our study suggests that achieving the WFD water quality goals may not enhance recreational ecosystem services, and calls for further empirical research on the connection between water quality and ecosystem services.

Real-Time Water Quality Management in the Grassland Water District

Energy Technology Data Exchange (ETDEWEB)

Quinn, Nigel W.T.; Hanna, W. Mark; Hanlon, Jeremy S.; Burns, Josphine R.; Taylor, Christophe M.; Marciochi, Don; Lower, Scott; Woodruff, Veronica; Wright, Diane; Poole, Tim

2004-12-10

The purpose of the research project was to advance the concept of real-time water quality management in the San Joaquin Basin by developing an application to drainage of seasonal wetlands in the Grassland Water District. Real-time water quality management is defined as the coordination of reservoir releases, return flows and river diversions to improve water quality conditions in the San Joaquin River and ensure compliance with State water quality objectives. Real-time water quality management is achieved through information exchange and cooperation between shakeholders who contribute or withdraw flow and salt load to or from the San Joaquin River. This project complements a larger scale project that was undertaken by members of the Water Quality Subcommittee of the San Joaquin River Management Program (SJRMP) and which produced forecasts of flow, salt load and San Joaquin River assimilative capacity between 1999 and 2003. These forecasts can help those entities exporting salt load to the River to develop salt load targets as a mechanism for improving compliance with salinity objectives. The mass balance model developed by this project is the decision support tool that helps to establish these salt load targets. A second important outcome of this project was the development and application of a methodology for assessing potential impacts of real-time wetland salinity management. Drawdown schedules are typically tied to weather conditions and are optimized in traditional practices to maximize food sources for over-wintering wildfowl as well as providing a biological control (through germination temperature) of undesirable weeds that compete with the more proteinaceous moist soil plants such as swamp timothy, watergrass and smartweed. This methodology combines high resolution remote sensing, ground-truthing vegetation surveys using established survey protocols and soil salinity mapping using rapid, automated electromagnetic sensor technology. This survey methodology

A GIS-based Model for Urban Change and Implications for Water Quality in the Pontchartrain Basin

Science.gov (United States)

Carstens, D.; Amer, R. M.

2017-12-01

The combination of remote sensing techniques and Geographic Information Systems (GIS) to measure water quality allows researchers to monitor changes in various water quality parameters over temporal and spatial scales that are not always readily apparent from in situ measurements. Water has a distinct spectral behavior in comparison to soil, vegetation and urban, and therefore can be distinguished from surrounding environments. This study involves using remote sensing and GIS methods to map urban sprawl and its resulting influences on water quality in the Pontchartrain Basin over the last three decades. Two images of Landsat Thematic Mapper (TM) were taken in October 1985 and two images of Landsat Operational Land Imager (OLI) were taken in 2015 were atmospherically corrected and processed to map urban sprawl and influences on water quality of Pontchartrain Basin in the last three decades. To accomplish this, a normalized difference building index (NDBI) was developed for Landsat images. The NDBI was calculated from (NIR - SWIR) / (NIR + SWIR), where SWIR is the longest wavelength. The normalized difference vegetation index (NDVI), the normalized difference soil index (NDSI), and the normalized difference water index (NDWI) were also calculated for Landsat images. A GIS model was developed by integrating the NDBI, NDVI, NDSI, and NDWI, and yielded urban/non-urban/water boundary maps with 30-m resolution. Results indicate that urban areas have increased approximately from 25,643 km2 to 26,677 km2, which represents about 4.0% change from non-urban to urban in the last 3 decades. The results are in a good agreement with the U.S. Census data, which indicated that there is a 12.25% increase in population over the last 25 years in the 16 parishes of the Pontchartrain Basin. Urban changes were compared with changes of water quality parameters in PONTCHARTRAIN BASIN, which include pH, specific conductance, nitrogen, phosphorous, and dissolved oxygen. The results show that

The derivation of water quality criteria of copper in Biliu River

Science.gov (United States)

Zheng, Hongbo; Jia, Xinru

2018-03-01

Excessive copper in water can be detrimental to the health of human and aquatic life. China has promulgated Environmental Quality Standards for Surface Water to control water pollution, but uniform standard values may cause under-protection or over-protection. Therefore, the basic research work on water quality criteria of water source or reservoir is urgently needed. This study deduces the acute and chronic Water Quality Criteria (WQC) of copper in Biliu River by Species Sensitivity Distribution method (SSD). The result shows that BiDoseResp is the most suitable model and the acute and chronic water quality benchmark of copper are 10.72 µg•L-1 and 5.86 µg•L-1. This study provides basis for the construction of water quality standard of Liaoning and the environmental management of Biliu River.

Assessing ecosystem effects of reservoir operations using food web-energy transfer and water quality models

Science.gov (United States)

Saito, L.; Johnson, B.M.; Bartholow, J.; Hanna, R.B.

2001-01-01

We investigated the effects on the reservoir food web of a new temperature control device (TCD) on the dam at Shasta Lake, California. We followed a linked modeling approach that used a specialized reservoir water quality model to forecast operation-induced changes in phytoplankton production. A food web–energy transfer model was also applied to propagate predicted changes in phytoplankton up through the food web to the predators and sport fishes of interest. The food web–energy transfer model employed a 10% trophic transfer efficiency through a food web that was mapped using carbon and nitrogen stable isotope analysis. Stable isotope analysis provided an efficient and comprehensive means of estimating the structure of the reservoir's food web with minimal sampling and background data. We used an optimization procedure to estimate the diet proportions of all food web components simultaneously from their isotopic signatures. Some consumers were estimated to be much more sensitive than others to perturbations to phytoplankton supply. The linked modeling approach demonstrated that interdisciplinary efforts enhance the value of information obtained from studies of managed ecosystems. The approach exploited the strengths of engineering and ecological modeling methods to address concerns that neither of the models could have addressed alone: (a) the water quality model could not have addressed quantitatively the possible impacts to fish, and (b) the food web model could not have examined how phytoplankton availability might change due to reservoir operations.

Comparing the Performance of Artificial Intelligence Models in Estimating Water Quality Parameters in Periods of Low and High Water Flow

Directory of Open Access Journals (Sweden)

majid montaseri

2017-03-01

Full Text Available Introduction: A total dissolved solid (TDS is an important indicator for water quality assesment. Since the composition of mineral salts and discharge affects the TDS of water, it is important to understand the relationships of mineral salts composition with TDS. Materials and Methods: In this study, methods of artificial neural networks with five different training algorithm,Levenberg-Marquardt (LM, Scaled Conjugate Gradient (SCG, Fletcher Conjugate Gradient (CGF, One Step Secant (OSS and Gradient descent with adaptive learning rate backpropagation(GDAalgorithm and adaptive Neurofuzzy inference system based on Subtractive Clustering were used to model water quality properties of Zarrineh River Basin, to be developed in total dissolved solids prediction. ANN and ANFIS program code were written in MATLAB language. Here, the ANN with one hidden layer was used and the hidden nodes’ number was determined using trial and error. Different activation functions (logarithm sigmoid, tangent sigmoid and linear were tried for the hidden and output nodes. Therefore, water quality data from seven hydrometer stationswere used during the statistical period of 18years (1993-2010.In this research, the study period was divided into two periods of dry and wet flow, and then in a preliminary statistical analysis, the main parameters affecting the estimation of the TDS are determined and isused for modeling. 75% of data are used for remaining and 25% of the data are used for evaluation of the model, randomly. In this paper, three statistical evaluation criteria, correlation coefficient (R, the root mean square error (RMSE and mean absolute error (MAE were used to assess models’ performances. Results and Discussion: By applying correlation coefficients method between the parameters of water quality and discharge with total dissolved solid in two periods, wet and dry periods, the significant (at 95% level variables entered into the model were Q, HCO3., Cl, So4, Ca

seasonal variation in water quality of orle river basin, sw nigeria.

African Journals Online (AJOL)

LUCY

The seasonal variation of water quality of Orle River and its tributatries in S.W. Nigeria was investigated forthnightly or two ... KEYWORD: water quality, river basin, wet and dry seasons; pollution. ..... Environmental Modeling and Software,.

WATER QUALITY INDEX FOR ASSESSMENT OF DRINKING WATER SOURCES FROM MEDIAŞ TOWN, SIBIU COUNTY

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ROŞU CRISTINA

2014-03-01

Full Text Available The purpose of this study was to evaluate the drinking water sources quality from Mediaş Town, Sibiu County. In November 2013, 6 water samples were taken from different drinking water sources and each water sample was analysed to determinate physico-chemical parameters (using a portable multiparameter WTW 320i major ions (using DIONEX ICS1500 ion chromatograph and heavy metals (using Atomic Absorption Spectrophotometer model ZENIT 700 Analytik Jena. The investigated physico-chemical parameters were: temperature, salinity, electrical conductivity (EC, pH, total dissolved solids (TDS and redox potential (ORP. The analysed major ions were: lithium (Li+, sodium (Na+, potassium (K+, magnesium (Mg2+, calcium (Ca2+, fluoride( F-, chloride (Cl-, bromide (Br-, nitrite (NO2-, nitrate (NO3-, phosphate (PO43- and sulphate (SO42-. The investigated heavy metals were: lead (Pb, zinc (Zn, cooper (Cu, iron (Fe, cadmium (Cd, nickel (Ni, chromium (Cr and arsenic (As. The Water Quality Index (WQI was calculated using the analysed water quality parameters and it ranged from 76 (very poor water quality to 375 (unsuitable for drinking.

Water quality assessment of selected domestic water sources in ...

African Journals Online (AJOL)

However, lead ion appears higher than the approved WHO and SON standard for water quality in all the sources except that of water vendors which is 0.04mg/l. It is therefore recommended that periodic monitoring of water quality, effective waste management system to improve the general water quality in the town, and ...

Hydrology and water quality of Shell Lake, Washburn County, Wisconsin, with special emphasis on the effects of diversion and changes in water level on the water quality of a shallow terminal lake

Science.gov (United States)

Juckem, Paul F.; Robertson, Dale M.

2013-01-01

Shell Lake is a relatively shallow terminal lake (tributaries but no outlets) in northwestern Wisconsin that has experienced approximately 10 feet (ft) of water-level fluctuation over more than 70 years of record and extensive flooding of nearshore areas starting in the early 2000s. The City of Shell Lake (City) received a permit from the Wisconsin Department of Natural Resources in 2002 to divert water from the lake to a nearby river in order to lower water levels and reduce flooding. Previous studies suggested that water-level fluctuations were driven by long-term cycles in precipitation, evaporation, and runoff, although questions about the lake’s connection with the groundwater system remained. The permit required that the City evaluate assumptions about lake/groundwater interactions made in previous studies and evaluate the effects of the water diversion on water levels in Shell Lake and other nearby lakes. Therefore, a cooperative study between the City and U.S. Geological Survey (USGS) was initiated to improve the understanding of the hydrogeology of the area and evaluate potential effects of the diversion on water levels in Shell Lake, the surrounding groundwater system, and nearby lakes. Concerns over deteriorating water quality in the lake, possibly associated with changes in water level, prompted an additional cooperative project between the City and the USGS to evaluate efeffects of changes in nutrient loading associated with changes in water levels on the water quality of Shell Lake. Numerical models were used to evaluate how the hydrology and water quality responded to diversion of water from the lake and historical changes in the watershed. The groundwater-flow model MODFLOW was used to simulate groundwater movement in the area around Shell Lake, including groundwater/surface-water interactions. Simulated results from the MODFLOW model indicate that groundwater flows generally northward in the area around Shell Lake, with flow locally converging

U.S. Midwestern Residents Perceptions of Water Quality

Directory of Open Access Journals (Sweden)

Lois Wright Morton

2011-02-01

Full Text Available The plurality of conservation and environmental viewpoints often challenge community leaders and government agency staff as they seek to engage citizens and build partnerships around watershed planning and management to solve complex water quality issues. The U.S. Midwest Heartland region (covering the states of Missouri, Kansa, Iowa, and Nebraska is dominated by row crop production and animal agriculture, where an understanding of perceptions held by residents of different locations (urban, rural non-farm, and rural farm towards water quality and the environment can provide a foundation for public deliberation and decision making. A stratified random sample mail survey of 1,042 Iowa, Kansas, Missouri, and Nebraska residents (54% response rate reveals many areas of agreement among farm, rural non-farm, and those who live in towns on the importance of water issues including the importance and use of water resources; beliefs about water quality and perceptions of impaired water quality causality; beliefs about protecting local waters; and environmental attitudes. With two ordinal logistic models, we also found that respondents with strong environmental attitudes have the least confidence in ground and surface water quality. The findings about differences and areas of agreement among the residents of different sectors can provide a communication bridge among divergent viewpoints and assist local leaders and agency staff as they seek to engage the public in discussions which lead to negotiating solutions to difficult water issues.

A three-dimensional water quality modeling approach for exploring the eutrophication responses to load reduction scenarios in Lake Yilong (China)

International Nuclear Information System (INIS)

Zhao, Lei; Li, Yuzhao; Zou, Rui; He, Bin; Zhu, Xiang; Liu, Yong; Wang, Junsong; Zhu, Yongguan

2013-01-01

Lake Yilong in Southwestern China has been under serious eutrophication threat during the past decades; however, the lake water remained clear until sudden sharp increase in Chlorophyll a (Chl a) and turbidity in 2009 without apparent change in external loading levels. To investigate the causes as well as examining the underlying mechanism, a three-dimensional hydrodynamic and water quality model was developed, simulating the flow circulation, pollutant fate and transport, and the interactions between nutrients, phytoplankton and macrophytes. The calibrated and validated model was used to conduct three sets of scenarios for understanding the water quality responses to various load reduction intensities and ecological restoration measures. The results showed that (a) even if the nutrient loads is reduced by as much as 77%, the Chl a concentration decreased only by 50%; and (b) aquatic vegetation has strong interaction with phytoplankton, therefore requiring combined watershed and in-lake management for lake restoration. -- Highlights: ► We quantitatively investigated the non-linear lake responses to load reduction. ► The aquatic ecological condition had a great impact on algal blooms. ► Only water quality improvement cannot ensure the aquatic ecology restoration. -- The lake water quality responds to watershed load reduction in a nonlinear way, which requires combined watershed and in-lake management for lake restoration

Water Quality Assessment and Management

Science.gov (United States)

Overview of Clean Water Act (CWA) restoration framework including; water quality standards, monitoring/assessment, reporting water quality status, TMDL development, TMDL implementation (point & nonpoint source control)

Urban water-quality modelling: implementing an extension to Multi-Hydro platform for real case studies

Science.gov (United States)

Hong, Yi; Giangola-Murzyn, Agathe; Bonhomme, Celine; Chebbo, Ghassan; Schertzer, Daniel

2015-04-01

During the last few years, the physically based and fully distributed numerical platform Multi-Hydro (MH) has been developed to simulate hydrological behaviours in urban/peri-urban areas (El-Tabach et al. , 2009 ; Gires et al., 2013 ; Giangola-Murzyn et al., 2014). This hydro-dynamical platform is open-access and has a modular structure, which is designed to be easily scalable and transportable, in order to simulate the dynamics and complex interactions of the water cycle processes in urban or peri-urban environment (surface hydrology, urban groundwater infrastructures and infiltration). Each hydrological module relies on existing and widely validated open source models, such as TREX model (Velleux, 2005) for the surface module, SWMM model (Rossman, 2010) for the drainage module and VS2DT model (Lappala et al., 1987) for the soil module. In our recent studies, an extension of MH has been set up by connecting the already available water-quality computational components among different modules, to introduce a pollutant transport modelling into the hydro-dynamical platform. As for the surface module in two-dimensions, the concentration of particles in flow is expressed by sediment advection equation, the settling of suspended particles is calculated with a simplified settling velocity formula, while the pollutant wash-off from a given land-use is represented as a mass rate of particle removal from the bottom boundary over time, based on transport capacity, which is computed by a modified form of Universal Soil Loss Equation (USLE). Considering that the USLE is originally conceived to predict soil losses caused by runoff in agriculture areas, several adaptations were needed to use it for urban areas, such as the alterations of USLE parameters according to different criterions, the definition of the appropriate initial dust thickness corresponding to various land-uses, etc. Concerning the drainage module, water quality routing within pipes assumes that the conduit

The Community Water Model (CWATM) / Development of a community driven global water model

Science.gov (United States)

Burek, Peter; Satoh, Yusuke; Greve, Peter; Kahil, Taher; Wada, Yoshihide

2017-04-01

With a growing population and economic development, it is expected that water demands will increase significantly in the future, especially in developing regions. At the same time, climate change is expected to alter spatial patterns of hydrological cycle and will have global, regional and local impacts on water availability. Thus, it is important to assess water supply, water demand and environmental needs over time to identify the populations and locations that will be most affected by these changes linked to water scarcity, droughts and floods. The Community Water Model (CWATM) will be designed for this purpose in that it includes an accounting of how future water demands will evolve in response to socioeconomic change and how water availability will change in response to climate. CWATM represents one of the new key elements of IIASA's Water program. It has been developed to work flexibly at both global and regional level at different spatial resolutions. The model is open source and community-driven to promote our work amongst the wider water community worldwide and is flexible enough linking to further planned developments such as water quality and hydro-economic modules. CWATM will be a basis to develop a next-generation global hydro-economic modeling framework that represents the economic trade-offs among different water management options over a basin looking at water supply infrastructure and demand managements. The integrated modeling framework will consider water demand from agriculture, domestic, energy, industry and environment, investment needs to alleviate future water scarcity, and will provide a portfolio of economically optimal solutions for achieving future water management options under the Sustainable Development Goals (SDG) for example. In addition, it will be able to track the energy requirements associated with the water supply system e.g., pumping, desalination and interbasin transfer to realize the linkage with the water-energy economy. In

Design of Cycle 3 of the National Water-Quality Assessment Program, 2013-23: Part 2: Science plan for improved water-quality information and management

Science.gov (United States)

Rowe, Gary L.; Belitz, Kenneth; Demas, Charlie R.; Essaid, Hedeff I.; Gilliom, Robert J.; Hamilton, Pixie A.; Hoos, Anne B.; Lee, Casey J.; Munn, Mark D.; Wolock, David W.

2013-01-01

This report presents a science strategy for the third decade of the National Water-Quality Assessment (NAWQA) Program, which since 1991, has been responsible for providing nationally consistent information on the quality of the Nation's streams and groundwater; how water quality is changing over time; and the major natural and human factors that affect current water quality conditions and trends. The strategy is based on an extensive evaluation of the accomplishments of NAWQA over its first two decades, the current status of water-quality monitoring activities by USGS and its partners, and an updated analysis of stakeholder priorities. The plan is designed to address priority issues and national needs identified by NAWQA stakeholders and the National Research Council (2012) irrespective of budget constraints. This plan describes four major goals for the third decade (Cycle 3), the approaches for monitoring, modeling, and scientific studies, key partnerships required to achieve these goals, and products and outcomes that will result from planned assessment activities. The science plan for 2013–2023 is a comprehensive approach to meet stakeholder priorities for: (1) rebuilding NAWQA monitoring networks for streams, rivers, and groundwater, and (2) upgrading models used to extrapolate and forecast changes in water-quality and stream ecosystem condition in response to changing climate and land use. The Cycle 3 plan continues approaches that have been central to the Program’s long-term success, but adjusts monitoring intensities and study designs to address critical information needs and identified data gaps. Restoration of diminished monitoring networks and new directions in modeling and interpretative studies address growing and evolving public and stakeholder needs for water-quality information and improved management, particularly in the face of increasing challenges related to population growth, increasing demands for water, and changing land use and climate

Application of chemometric methods for assessment and modelling of microbiological quality data concerning coastal bathing water in Greece

Directory of Open Access Journals (Sweden)

Agelos Papaioannou

2014-12-01

Full Text Available Background. Worldwide, the aim of managing water is to safeguard human health whilst maintaining sustainable aquatic and associated terrestrial, ecosystems. Because human enteric viruses are the most likely pathogens responsible for waterborne diseases from recreational water use, but detection methods are complex and costly for routine monitoring, it is of great interest to determine the quality of coastal bathing water with a minimum cost and maximum safety. Design and methods. This study handles the assessment and modelling of the microbiological quality data of 2149 seawater bathing areas in Greece over 10-year period (1997-2006 by chemometric methods. Results. Cluster analysis results indicated that the studied bathing beaches are classified in accordance with the seasonality in three groups. Factor analysis was applied to investigate possible determining factors in the groups resulted from the cluster analysis, and also two new parameters were created in each group; VF1 includes E. coli, faecal coliforms and total coliforms and VF2 includes faecal streptococci/enterococci. By applying the cluster analysis in each seasonal group, three new groups of coasts were generated, group A (ultraclean, group B (clean and group C (contaminated. Conclusions. The above analysis is confirmed by the application of discriminant analysis, and proves that chemometric methods are useful tools for assessment and modeling microbiological quality data of coastal bathing water on a large scale, and thus could attribute to effective and economical monitoring of the quality of coastal bathing water in a country with a big number of bathing coasts, like Greece.

How does higher frequency monitoring data affect the calibration of a process-based water quality model?

Science.gov (United States)

Jackson-Blake, Leah; Helliwell, Rachel

2015-04-01

Process-based catchment water quality models are increasingly used as tools to inform land management. However, for such models to be reliable they need to be well calibrated and shown to reproduce key catchment processes. Calibration can be challenging for process-based models, which tend to be complex and highly parameterised. Calibrating a large number of parameters generally requires a large amount of monitoring data, spanning all hydrochemical conditions. However, regulatory agencies and research organisations generally only sample at a fortnightly or monthly frequency, even in well-studied catchments, often missing peak flow events. The primary aim of this study was therefore to investigate how the quality and uncertainty of model simulations produced by a process-based, semi-distributed catchment model, INCA-P (the INtegrated CAtchment model of Phosphorus dynamics), were improved by calibration to higher frequency water chemistry data. Two model calibrations were carried out for a small rural Scottish catchment: one using 18 months of daily total dissolved phosphorus (TDP) concentration data, another using a fortnightly dataset derived from the daily data. To aid comparability, calibrations were carried out automatically using the Markov Chain Monte Carlo - DiffeRential Evolution Adaptive Metropolis (MCMC-DREAM) algorithm. Calibration to daily data resulted in improved simulation of peak TDP concentrations and improved model performance statistics. Parameter-related uncertainty in simulated TDP was large when fortnightly data was used for calibration, with a 95% credible interval of 26 μg/l. This uncertainty is comparable in size to the difference between Water Framework Directive (WFD) chemical status classes, and would therefore make it difficult to use this calibration to predict shifts in WFD status. The 95% credible interval reduced markedly with the higher frequency monitoring data, to 6 μg/l. The number of parameters that could be reliably auto

Quality-assurance and data-management plan for water-quality activities in the Kansas Water Science Center, 2014

Science.gov (United States)

Rasmussen, Teresa J.; Bennett, Trudy J.; Foster, Guy M.; Graham, Jennifer L.; Putnam, James E.

2014-01-01

As the Nation’s largest water, earth, and biological science and civilian mapping information agency, the U.S. Geological Survey is relied on to collect high-quality data, and produce factual and impartial interpretive reports. This quality-assurance and data-management plan provides guidance for water-quality activities conducted by the Kansas Water Science Center. Policies and procedures are documented for activities related to planning, collecting, storing, documenting, tracking, verifying, approving, archiving, and disseminating water-quality data. The policies and procedures described in this plan complement quality-assurance plans for continuous water-quality monitoring, surface-water, and groundwater activities in Kansas.

Application of Nemerow Index Method and Integrated Water Quality Index Method in Water Quality Assessment of Zhangze Reservoir

Science.gov (United States)

Zhang, Qian; Feng, Minquan; Hao, Xiaoyan

2018-03-01

[Objective] Based on the water quality historical data from the Zhangze Reservoir from the last five years, the water quality was assessed by the integrated water quality identification index method and the Nemerow pollution index method. The results of different evaluation methods were analyzed and compared and the characteristics of each method were identified.[Methods] The suitability of the water quality assessment methods were compared and analyzed, based on these results.[Results] the water quality tended to decrease over time with 2016 being the year with the worst water quality. The sections with the worst water quality were the southern and northern sections.[Conclusion] The results produced by the traditional Nemerow index method fluctuated greatly in each section of water quality monitoring and therefore could not effectively reveal the trend of water quality at each section. The combination of qualitative and quantitative measures of the comprehensive pollution index identification method meant it could evaluate the degree of water pollution as well as determine that the river water was black and odorous. However, the evaluation results showed that the water pollution was relatively low.The results from the improved Nemerow index evaluation were better as the single indicators and evaluation results are in strong agreement; therefore the method is able to objectively reflect the water quality of each water quality monitoring section and is more suitable for the water quality evaluation of the reservoir.

Influence of the South-North Water Diversion Project and the mitigation projects on the water quality of Han River.

Science.gov (United States)

Zhu, Y P; Zhang, H P; Chen, L; Zhao, J F

2008-11-15

Situated in the central part of China, the Han River Basin is undergoing rapid social and economic development with some human interventions to be made soon which will profoundly influence the water environment of the basin. The integrated MIKE 11 model system comprising of a rainfall-runoff model (NAM), a non-point load evaluation model (LOAD), a hydrodynamic model (MIKE 11 HD) and a water quality model (ECOLab) was applied to investigate the impact of the Middle Route of the South-North Water Diversion Project on the Han River and the effectiveness of the 2 proposed mitigation projects, the 22 wastewater treatment plants (WWTPs) and the Yangtze-Han Water Diversion Project. The study concludes that business as usual will lead to a continuing rapid deterioration of the water quality of the Han River. Implementation of the Middle Route of the South-North Water Diversion Project in 2010 will bring disastrous consequence in the form of the remarkably elevated pollution level and high risk of algae bloom in the middle and lower reaches. The proposed WWTPs will merely lower the pollution level in the reach by around 10%, while the Yangtze-Han Water Diversion Project can significantly improve the water quality in the downstream 200-km reach. The results reveal that serious water quality problem will emerge in the middle reach between Xiangfan and Qianjiang in the future. Implementation of the South-North Water Diversion Project (phase II) in 2030 will further exacerbate the problem. In order to effectively improve the water quality of the Han River, it is suggested that nutrient removal processes should be adopted in the proposed WWTPs, and the pollution load from the non-point sources, especially the load from the upstream Henan Province, should be effectively controlled.

[Drinking water quality and safety].

Science.gov (United States)

Gómez-Gutiérrez, Anna; Miralles, Maria Josepa; Corbella, Irene; García, Soledad; Navarro, Sonia; Llebaria, Xavier

2016-11-01

The purpose of drinking water legislation is to guarantee the quality and safety of water intended for human consumption. In the European Union, Directive 98/83/EC updated the essential and binding quality criteria and standards, incorporated into Spanish national legislation by Royal Decree 140/2003. This article reviews the main characteristics of the aforementioned drinking water legislation and its impact on the improvement of water quality against empirical data from Catalonia. Analytical data reported in the Spanish national information system (SINAC) indicate that water quality in Catalonia has improved in recent years (from 88% of analytical reports in 2004 finding drinking water to be suitable for human consumption, compared to 95% in 2014). The improvement is fundamentally attributed to parameters concerning the organoleptic characteristics of water and parameters related to the monitoring of the drinking water treatment process. Two management experiences concerning compliance with quality standards for trihalomethanes and lead in Barcelona's water supply are also discussed. Finally, this paper presents some challenges that, in the opinion of the authors, still need to be incorporated into drinking water legislation. It is necessary to update Annex I of Directive 98/83/EC to integrate current scientific knowledge, as well as to improve consumer access to water quality data. Furthermore, a need to define common criteria for some non-resolved topics, such as products and materials in contact with drinking water and domestic conditioning equipment, has also been identified. Copyright © 2016 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Post-fire Water Quality Response and Associated Physical Drivers

Science.gov (United States)

Rust, A.; Saxe, S.; Hogue, T. S.; McCray, J. E.; Rhoades, C.

2017-12-01

. Ultimately, improved understanding of post-fire response and related drivers will advance potential mitigation and treatment strategies as well as aid in the parametrization of post-fire models of water quality.

[Coupling SWAT and CE-QUAL-W2 models to simulate water quantity and quality in Shanmei Reservoir watershed].

Science.gov (United States)

Liu, Mei-Bing; Chen, Dong-Ping; Chen, Xing-Wei; Chen, Ying

2013-12-01

A coupled watershed-reservoir modeling approach consisting of a watershed distributed model (SWAT) and a two-dimensional laterally averaged model (CE-QUAL-W2) was adopted for simulating the impact of non-point source pollution from upland watershed on water quality of Shanmei Reservoir. Using the daily serial output from Shanmei Reservoir watershed by SWAT as the input to Shanmei Reservoir by CE-QUAL-W2, the coupled modeling was calibrated for runoff and outputs of sediment and pollutant at watershed scale and for elevation, temperature, nitrate, ammonium and total nitrogen in Shanmei Reservoir. The results indicated that the simulated values agreed fairly well with the observed data, although the calculation precision of downstream model would be affected by the accumulative errors generated from the simulation of upland model. The SWAT and CE-QUAL-W2 coupled modeling could be used to assess the hydrodynamic and water quality process in complex watershed comprised of upland watershed and downstream reservoir, and might further provide scientific basis for positioning key pollution source area and controlling the reservoir eutrophication.

Modelling and Analysis of Hydrodynamics and Water Quality for Rivers in the Northern Cold Region of China.

Science.gov (United States)

Tang, Gula; Zhu, Yunqiang; Wu, Guozheng; Li, Jing; Li, Zhao-Liang; Sun, Jiulin

2016-04-08

In this study, the Mudan River, which is the most typical river in the northern cold region of China was selected as the research object; Environmental Fluid Dynamics Code (EFDC) was adopted to construct a new two-dimensional water quality model for the urban sections of the Mudan River, and concentrations of COD(Cr) and NH₃N during ice-covered and open-water periods were simulated and analyzed. Results indicated that roughness coefficient and comprehensive pollutant decay rate were significantly different in those periods. To be specific, the roughness coefficient in the ice-covered period was larger than that of the open-water period, while the decay rate within the former period was smaller than that in the latter. In addition, according to the analysis of the simulated results, the main reasons for the decay rate reduction during the ice-covered period are temperature drop, upstream inflow decrease and ice layer cover; among them, ice sheet is the major contributor of roughness increase. These aspects were discussed in more detail in this work. The model could be generalized to hydrodynamic water quality process simulation researches on rivers in other cold regions as well.

Modelling and Analysis of Hydrodynamics and Water Quality for Rivers in the Northern Cold Region of China

Directory of Open Access Journals (Sweden)

Gula Tang

2016-04-01

Full Text Available In this study, the Mudan River, which is the most typical river in the northern cold region of China was selected as the research object; Environmental Fluid Dynamics Code (EFDC was adopted to construct a new two-dimensional water quality model for the urban sections of the Mudan River, and concentrations of CODCr and NH3N during ice-covered and open-water periods were simulated and analyzed. Results indicated that roughness coefficient and comprehensive pollutant decay rate were significantly different in those periods. To be specific, the roughness coefficient in the ice-covered period was larger than that of the open-water period, while the decay rate within the former period was smaller than that in the latter. In addition, according to the analysis of the simulated results, the main reasons for the decay rate reduction during the ice-covered period are temperature drop, upstream inflow decrease and ice layer cover; among them, ice sheet is the major contributor of roughness increase. These aspects were discussed in more detail in this work. The model could be generalized to hydrodynamic water quality process simulation researches on rivers in other cold regions as well.

Effects of Coordinated Operation of Weirs and Reservoirs on the Water Quality of the Geum River

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Jung Min Ahn

2017-06-01

Full Text Available Multifunctional weirs can be used to maintain water supply during dry seasons and to improve downstream water quality during drought conditions through discharge based on retained flux. Sixteen multifunctional weirs were recently constructed in four river systems as part of the Four Rivers Restoration Project. In this study, three multifunctional weirs in the Geum River Basin were investigated to analyze the environmental effects of multifunctional weir operation on downstream flow. To determine seasonal vulnerability to drought, the basin was evaluated using the Palmer Drought Severity Index (PDSI. Furthermore, the downstream flow regime and the effect on water quality improvement of a coordinated dam–multifunctional weir operation controlled by: (a a rainfall–runoff model; (b a reservoir optimization model; and (c a water quality model, were examined. A runoff estimate at each major location in the Geum River Basin was performed using the water quality model, and examined variation in downstream water quality depending on the operational scenario of each irrigation facility such as dams and weirs. Although the water quality was improved by the coordinated operation of the dams and weirs, when the discharged water quality is poor, the downstream water quality is not improved. Therefore, it is necessary to first improve the discharged water quality on the lower Geum River. Improvement of the water quality of main stream in the Geum River is important, but water quality from tributaries should also be improved. By applying the estimated runoff data to the reservoir optimization model, these scenarios will be utilized as basic parameters for assessing the optimal operation of the river.

18 CFR 801.7 - Water quality.

Science.gov (United States)

2010-04-01

... 18 Conservation of Power and Water Resources 2 2010-04-01 2010-04-01 false Water quality. 801.7... POLICIES § 801.7 Water quality. (a) The signatory States have the primary responsibility in the basin for water quality management and control. However, protection of the water resources of the basin from...

SWIM (Soil and Water Integrated Model)

Energy Technology Data Exchange (ETDEWEB)

Krysanova, V; Wechsung, F; Arnold, J; Srinivasan, R; Williams, J

2000-12-01

The model SWIM (Soil and Water Integrated Model) was developed in order to provide a comprehensive GIS-based tool for hydrological and water quality modelling in mesoscale and large river basins (from 100 to 10,000 km{sup 2}), which can be parameterised using regionally available information. The model was developed for the use mainly in Europe and temperate zone, though its application in other regions is possible as well. SWIM is based on two previously developed tools - SWAT and MATSALU (see more explanations in section 1.1). The model integrates hydrology, vegetation, erosion, and nutrient dynamics at the watershed scale. SWIM has a three-level disaggregation scheme 'basin - sub-basins - hydrotopes' and is coupled to the Geographic Information System GRASS (GRASS, 1993). A robust approach is suggested for the nitrogen and phosphorus modelling in mesoscale watersheds. SWIM runs under the UNIX environment. Model test and validation were performed sequentially for hydrology, crop growth, nitrogen and erosion in a number of mesoscale watersheds in the German part of the Elbe drainage basin. A comprehensive scheme of spatial disaggregation into sub-basins and hydrotopes combined with reasonable restriction on a sub-basin area allows performing the assessment of water resources and water quality with SWIM in mesoscale river basins. The modest data requirements represent an important advantage of the model. Direct connection to land use and climate data provides a possibility to use the model for analysis of climate change and land use change impacts on hydrology, agricultural production, and water quality. (orig.)

Predicting fire effects on water quality: a perspective and future needs

Science.gov (United States)

Smith, Hugh; Sheridan, Gary; Nyman, Petter; Langhans, Christoph; Noske, Philip; Lane, Patrick

2017-04-01

Forest environments are a globally significant source of drinking water. Fire presents a credible threat to the supply of high quality water in many forested regions. The post-fire risk to water supplies depends on storm event characteristics, vegetation cover and fire-related changes in soil infiltration and erodibility modulated by landscape position. The resulting magnitude of runoff generation, erosion and constituent flux to streams and reservoirs determines the severity of water quality impacts in combination with the physical and chemical composition of the entrained material. Research to date suggests that most post-fire water quality impacts are due to large increases in the supply of particulates (fine-grained sediment and ash) and particle-associated chemical constituents. The largest water quality impacts result from high magnitude erosion events, including debris flow processes, which typically occur in response to short duration, high intensity storm events during the recovery period. Most research to date focuses on impacts on water quality after fire. However, information on potential water quality impacts is required prior to fire events for risk planning. Moreover, changes in climate and forest management (e.g. prescribed burning) that affect fire regimes may alter water quality risks. Therefore, prediction requires spatial-temporal representation of fire and rainfall regimes coupled with information on fire-related changes to soil hydrologic parameters. Recent work has applied such an approach by combining a fire spread model with historic fire weather data in a Monte Carlo simulation to quantify probabilities associated with fire and storm events generating debris flows and fine sediment influx to a reservoir located in Victoria, Australia. Prediction of fire effects on water quality would benefit from further research in several areas. First, more work on regional-scale stochastic modelling of intersecting fire and storm events with landscape

Topological clustering as a tool for planning water quality monitoring in water distribution networks

DEFF Research Database (Denmark)

Kirstein, Jonas Kjeld; Albrechtsen, Hans-Jørgen; Rygaard, Martin

2015-01-01

) identify steady clusters for a part of the network where an actual contamination has occurred; (2) analyze this event by the use of mesh diagrams; and (3) analyze the use of mesh diagrams as a decision support tool for planning water quality monitoring. Initially, the network model was divided...... into strongly and weakly connected clusters for selected time periods and mesh diagrams were used for analysing cluster connections in the Nørrebro district. Here, areas of particular interest for water quality monitoring were identified by including user-information about consumption rates and consumers...... particular sensitive towards water quality deterioration. The analysis revealed sampling locations within steady clusters, which increased samples' comparability over time. Furthermore, the method provided a simplified overview of water movement in complex distribution networks, and could assist...

Seasonal variations of ground water quality and its agglomerates by water quality index

Directory of Open Access Journals (Sweden)

S. Sharma

2016-01-01

Full Text Available Water is a unique natural resource among all sources available on earth. It plays an important role in economic development and the general well-being of the country. This study aimed at using the application of water quality index in evaluating the ground water quality innorth-east area of Jaipur in pre and post monsoon for public usage. Total eleven physico–chemical characteristics; total dissolved solids, total hardness,chloride, nitrate, electrical conductance, sodium, fluorideand potassium, pH, turbidity, temperature were analyzed and observed values were compared with standard values recommended by Indian standard and World Health Organization. Most of parameter show higher value than permissible limit in pre and post monsoon. Water quality index study showed that drinking water in Amer (221.58,277.70, Lalawas (362.74,396.67, Jaisinghpura area (286.00,273.78 were found to be highly contaminated due to high value of total dissolved solids, electrical conductance, total hardness, chloride, nitrate and sodium.Saipura (122.52, 131.00, Naila (120.25, 239.86, Galta (160.9, 204.1 were found to be moderately contaminated for both monsoons. People dependent on this water may prone to health hazard. Therefore some effective measures are urgently required to enhance the quality of water in these areas.

Seasonal variations of ground water quality and its agglomerates by water quality index

International Nuclear Information System (INIS)

Sharma, S.; Chhipa, R.C.

2016-01-01

Water is a unique natural resource among all sources available on earth. It plays an important role in economic development and the general well-being of the country. This study aimed at using the application of water quality index in evaluating the ground water quality in north-east area of Jaipur in pre and post monsoon for public usage. Total eleven physico–chemical characteristics; total dissolved solids, total hardness,chloride, nitrate, electrical conductance, sodium, fluoride and potassium, p H, turbidity, temperature) were analyzed and observed values were compared with standard values recommended by Indian standard and World Health Organization. Most of parameter show higher value than permissible limit in pre and post monsoon. Water quality index study showed that drinking water in Amer (221.58,277.70), Lalawas (362.74,396.67), Jaisinghpura area (286.00, 273.78) were found to be highly contaminated due to high value of total dissolved solids, electrical conductance, total hardness, chloride, nitrate and sodium. Saipura (122.52, 131.00), Naila (120.25, 239.86), Galta (160.9, 204.1) were found to be moderately contaminated for both monsoons. People dependent on this water may prone to health hazard. Therefore some effective measures are urgently required to enhance the quality of water in these areas.

Critical review: Radionuclide transport, sediment transport, and water quality mathematical modeling; and radionuclide adsorption/desorption mechanisms

Energy Technology Data Exchange (ETDEWEB)

Onishi, Y.; Serne, R.J.; Arnold, E.M.; Cowan, C.E.; Thompson, F.L. [Pacific Northwest Lab., Richland, WA (United States)

1981-01-01

This report describes the results of a detailed literature review of radionuclide transport models applicable to rivers, estuaries, coastal waters, the Great Lakes, and impoundments. Some representatives sediment transport and water quality models were also reviewed to evaluate if they can be readily adapted to radionuclide transport modeling. The review showed that most available transport models were developed for dissolved radionuclide in rivers. These models include the mechanisms of advection, dispersion, and radionuclide decay. Since the models do not include sediment and radionuclide interactions, they are best suited for simulating short-term radionuclide migration where: (1) radionuclides have small distribution coefficients; (2) sediment concentrations in receiving water bodies are very low. Only 5 of the reviewed models include full sediment and radionuclide interactions: CHMSED developed by Fields; FETRA SERATRA, and TODAM developed by Onishi et al, and a model developed by Shull and Gloyna. The 5 models are applicable to cases where: (1) the distribution coefficient is large; (2) sediment concentrations are high; or (3) long-term migration and accumulation are under consideration. The report also discusses radionuclide absorption/desorption distribution ratios and addresses adsorption/desorption mechanisms and their controlling processes for 25 elements under surface water conditions. These elements are: Am, Sb, C, Ce, Cm, Co, Cr, Cs, Eu, I, Fe, Mn, Np, P, Pu, Pm, Ra, Ru, Sr, Tc, Th, {sup 3}H, U, Zn and Zr.

Small drinking water systems under spatiotemporal water quality variability: a risk-based performance benchmarking framework.

Science.gov (United States)

Bereskie, Ty; Haider, Husnain; Rodriguez, Manuel J; Sadiq, Rehan

2017-08-23

Traditional approaches for benchmarking drinking water systems are binary, based solely on the compliance and/or non-compliance of one or more water quality performance indicators against defined regulatory guidelines/standards. The consequence of water quality failure is dependent on location within a water supply system as well as time of the year (i.e., season) with varying levels of water consumption. Conventional approaches used for water quality comparison purposes fail to incorporate spatiotemporal variability and degrees of compliance and/or non-compliance. This can lead to misleading or inaccurate performance assessment data used in the performance benchmarking process. In this research, a hierarchical risk-based water quality performance benchmarking framework is proposed to evaluate small drinking water systems (SDWSs) through cross-comparison amongst similar systems. The proposed framework (R WQI framework) is designed to quantify consequence associated with seasonal and location-specific water quality issues in a given drinking water supply system to facilitate more efficient decision-making for SDWSs striving for continuous performance improvement. Fuzzy rule-based modelling is used to address imprecision associated with measuring performance based on singular water quality guidelines/standards and the uncertainties present in SDWS operations and monitoring. This proposed R WQI framework has been demonstrated using data collected from 16 SDWSs in Newfoundland and Labrador and Quebec, Canada, and compared to the Canadian Council of Ministers of the Environment WQI, a traditional, guidelines/standard-based approach. The study found that the R WQI framework provides an in-depth state of water quality and benchmarks SDWSs more rationally based on the frequency of occurrence and consequence of failure events.

How is the River Water Quality Response to Climate Change Impacts?

Science.gov (United States)

Nguyen, T. T.; Willems, P.

2015-12-01

Water quality and its response to climate change have been become one of the most important issues of our society, which catches the attention of many scientists, environmental activists and policy makers. Climate change influences the river water quality directly and indirectly via rainfall and air temperature. For example, low flow decreases the volume of water for dilution and increases the residence time of the pollutants. By contrast, high flow leads to increases in the amount of pollutants and sediment loads from catchments to rivers. The changes in hydraulic characteristics, i.e. water depth and velocity, affect the transportation and biochemical transformation of pollutants in the river water body. The high air temperature leads to increasing water temperature, shorter growing periods of different crops and water demands from domestic households and industries, which eventually effects the level of river pollution. This study demonstrates the quantification of the variation of the water temperature and pollutant concentrations along the Molse Neet river in the North East of Belgium as a result of the changes in the catchment rainfall-runoff, air temperature and nutrient loads. Firstly, four climate change scenarios were generated based on a large ensemble of available global and regional climate models and statistical downscaling based on a quantile perturbation method. Secondly, the climatic changes to rainfall and temperature were transformed to changes in the evapotranspiration and runoff flow through the conceptual hydrological model PDM. Thirdly, the adjustment in nutrient loads from agriculture due to rainfall and growing periods of crops were calculated by means of the semi-empirical SENTWA model. Water temperature was estimated from air temperature by a stochastic model separating the temperature into long-term annual and short-term residual components. Next, hydrodynamic and water quality models of the river, implemented in InfoWorks RS, were

Modeling Relationships between Surface Water Quality and Landscape Metrics Using the Adaptive Neuro-Fuzzy Inference System, A Case Study in Mazandaran Province

Directory of Open Access Journals (Sweden)

mohsen Mirzayi

2016-03-01

Full Text Available Landscape indices can be used as an approach for predicting water quality changes to monitor non-point source pollution. In the present study, the data collected over the period from 2012 to 2013 from 81 water quality stations along the rivers flowing in Mazandaran Province were analyzed. Upstream boundries were drawn and landscape metrics were extracted for each of the sub-watersheds at class and landscape levels. Principal component analysis was used to single out the relevant water quality parameters and forward linear regression was employed to determine the optimal metrics for the description of each parameter. The first five components were able to describe 96.61% of the variation in water quality in Mazandaran Province. Adaptive Neuro-fuzzy Inference System (ANFIS and multiple linear regression were used to model the relationship between landscape metrics and water quality parameters. The results indicate that multiple regression was able to predict SAR, TDS, pH, NO3‒, and PO43‒ in the test step, with R2 values equal to 0.81, 0.56, 0.73, 0.44. and 0.63, respectively. The corresponding R2 value of ANFIS in the test step were 0.82, 0.79, 0.82, 0.31, and 0.36, respectively. Clearly, ANFIS exhibited a better performance in each case than did the linear regression model. This indicates a nonlinear relationship between the water quality parameters and landscape metrics. Since different land cover/uses have considerable impacts on both the outflow water quality and the available and dissolved pollutants in rivers, the method can be reasonably used for regional planning and environmental impact assessment in development projects in the region.

Trend analysis of a tropical urban river water quality in Malaysia.

Science.gov (United States)

Othman, Faridah; M E, Alaa Eldin; Mohamed, Ibrahim

2012-12-01

Rivers play a significant role in providing water resources for human and ecosystem survival and health. Hence, river water quality is an important parameter that must be preserved and monitored. As the state of Selangor and the city of Kuala Lumpur, Malaysia, are undergoing tremendous development, the river is subjected to pollution from point and non-point sources. The water quality of the Klang River basin, one of the most densely populated areas within the region, is significantly degraded due to human activities as well as urbanization. Evaluation of the overall river water quality status is normally represented by a water quality index (WQI), which consists of six parameters, namely dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, suspended solids, ammoniacal nitrogen and pH. The objectives of this study are to assess the water quality status for this tropical, urban river and to establish the WQI trend. Using monthly WQI data from 1997 to 2007, time series were plotted and trend analysis was performed by employing the first-order autocorrelated trend model on the moving average values for every station. The initial and final values of either the moving average or the trend model were used as the estimates of the initial and final WQI at the stations. It was found that Klang River water quality has shown some improvement between 1997 and 2007. Water quality remains good in the upper stream area, which provides vital water sources for water treatment plants in the Klang valley. Meanwhile, the water quality has also improved in other stations. Results of the current study suggest that the present policy on managing river quality in the Klang River has produced encouraging results; the policy should, however, be further improved alongside more vigorous monitoring of pollution discharge from various point sources such as industrial wastewater, municipal sewers, wet markets, sand mining and landfills, as well as non-point sources such as

Logistic and linear regression model documentation for statistical relations between continuous real-time and discrete water-quality constituents in the Kansas River, Kansas, July 2012 through June 2015

Science.gov (United States)

Foster, Guy M.; Graham, Jennifer L.

2016-04-06

The Kansas River is a primary source of drinking water for about 800,000 people in northeastern Kansas. Source-water supplies are treated by a combination of chemical and physical processes to remove contaminants before distribution. Advanced notification of changing water-quality conditions and cyanobacteria and associated toxin and taste-and-odor compounds provides drinking-water treatment facilities time to develop and implement adequate treatment strategies. The U.S. Geological Survey (USGS), in cooperation with the Kansas Water Office (funded in part through the Kansas State Water Plan Fund), and the City of Lawrence, the City of Topeka, the City of Olathe, and Johnson County Water One, began a study in July 2012 to develop statistical models at two Kansas River sites located upstream from drinking-water intakes. Continuous water-quality monitors have been operated and discrete-water quality samples have been collected on the Kansas River at Wamego (USGS site number 06887500) and De Soto (USGS site number 06892350) since July 2012. Continuous and discrete water-quality data collected during July 2012 through June 2015 were used to develop statistical models for constituents of interest at the Wamego and De Soto sites. Logistic models to continuously estimate the probability of occurrence above selected thresholds were developed for cyanobacteria, microcystin, and geosmin. Linear regression models to continuously estimate constituent concentrations were developed for major ions, dissolved solids, alkalinity, nutrients (nitrogen and phosphorus species), suspended sediment, indicator bacteria (Escherichia coli, fecal coliform, and enterococci), and actinomycetes bacteria. These models will be used to provide real-time estimates of the probability that cyanobacteria and associated compounds exceed thresholds and of the concentrations of other water-quality constituents in the Kansas River. The models documented in this report are useful for characterizing changes

40 CFR 130.3 - Water quality standards.

Science.gov (United States)

2010-07-01

... 40 Protection of Environment 21 2010-07-01 2010-07-01 false Water quality standards. 130.3 Section... QUALITY PLANNING AND MANAGEMENT § 130.3 Water quality standards. A water quality standard (WQS) defines the water quality goals of a water body, or portion thereof, by designating the use or uses to be made...

Predicting the Effects of Water Quality on the Growth of Thalassia testudinum in Tampa Bay with a Dynamic Simile-Based Model Tool

Science.gov (United States)

We describe a seagrass growth (SGG) model that is coupled to a water quality (WQ) model that includes the effects of phytoplankton (chlorophyll), colored dissolved organic matter (CDOM) and suspended solids (TSS) on water clarity. Phytoplankton growth was adjusted daily for PAR (...

Can There Ever Be Enough to Impact Water Quality? Evaluating BMPs in Elliot Ditch, Indiana Using the LTHIA-LID Model

Science.gov (United States)

Rahman, M. S.; Hoover, F. A.; Bowling, L. C.

2017-12-01

Elliot Ditch is an urban/urbanizing watershed located in the city of Lafayette, IN, USA. The city continues to struggle with stormwater management and combined sewer overflow (CSO) events. Several best-management practices (BMP) such as rain gardens, green roofs, and bioswales have been implemented in the watershed, but the level of adoption needed to achieve meaningful impact is currently unknown. This study's goal is to determine what level of BMP coverage is needed to impact water quality, whether meaningful impact is determined by achieving water quality targets or statistical significance. A power analysis was performed using water quality data for total suspended solids (TSS), E.coli, total phosphorus (TP) and nitrate (NO3-N) from Elliot Ditch from 2011 to 2015. The minimum detectable difference (MDD) was calculated as the percent reduction in load needed to detect a significant change in the watershed. The water quality targets were proposed by stakeholders as part of a watershed management planning process. The water quality targets and the MDD percentages were then compared to simulated load reductions due to BMP implementation using the Long-term Hydrologic Impact Assessment-Low Impact Development (LTHIA-LID) model. Seven baseline model scenarios were simulated by implementing the maximum number of each of six types of BMPs (rain barrels, permeable patios, green roofs, grassed swale/bioswales, bioretention/rain gardens, and porous pavement), as well as all the practices combined in the watershed. These provide the baseline for targeted implementation scenarios designed to determine if statistically and physically meaningful load reductions can be achieved through BMP implementation alone.

Climate Change Impact Assessment for Sustainable Water Quality Management

Directory of Open Access Journals (Sweden)

Ching-Pin Tung

2012-01-01

Full Text Available The goal of sustainable water quality management is to keep total pollutant discharges from exceeding the assimilation capacity of a water body. Climate change may influence streamflows, and further alter assimilation capacity and degrade river sustainability. The purposes of this study are to evaluate the effect of climate change on sustainable water quality management and design an early warning indicator to issue warnings on river sustainability. A systematic assessment procedure is proposed here, including a weather generation model, the streamflow component of GWLF, QUAL2E, and an optimization model. The Touchen creek in Taiwan is selected as the study area. Future climate scenarios derived from projections of four global climate models (GCMs and two pollutant discharge scenarios, as usual and proportional to population, are considered in this study. The results indicate that streamflows may very likely increase in humid seasons and decrease in arid seasons, respectively. The reduction of streamflow in arid seasons may further degrade water quality and assimilation capacity. In order to provide warnings to trigger necessary adaptation strategies, an early warning indicator is designed and its 30-year moving average is calculated. Finally, environmental monitoring systems and methods to prioritize adaptation strategies are discussed for further studies in the future.

The water quality of the LOCAR Pang and Lambourn catchments

Directory of Open Access Journals (Sweden)

C. Neal

2004-01-01

Full Text Available The water quality of the Pang and Lambourn, tributaries of the River Thames, in south-eastern England, is described in relation to spatial and temporal dimensions. The river waters are supplied mainly from Chalk-fed aquifer sources and are, therefore, of a calcium-bicarbonate type. The major, minor and trace element chemistry of the rivers is controlled by a combination of atmospheric and pollutant inputs from agriculture and sewage sources superimposed on a background water quality signal linked to geological sources. Water quality does not vary greatly over time or space. However, in detail, there are differences in water quality between the Pang and Lambourn and between sites along the Pang and the Lambourn. These differences reflect hydrological processes, water flow pathways and water quality input fluxes. The Pang’s pattern of water quality change is more variable than that of the Lambourn. The flow hydrograph also shows both a cyclical and 'uniform pattern' characteristic of aquifer drainage with, superimposed, a series of 'flashier' spiked responses characteristic of karstic systems. The Lambourn, in contrast, shows simpler features without the 'flashier' responses. The results are discussed in relation to the newly developed UK community programme LOCAR dealing with Lowland Catchment Research. A descriptive and box model structure is provided to describe the key features of water quality variations in relation to soil, unsaturated and groundwater flows and storage both away from and close to the river. Keywords: water quality, nitrate, ammonium, phosphorus, pH, alkalinity, nutrients, major elements, trace elements, rainfall, river, Pang, Lambourn, LOCAR

Modeling the relationship between landscape characteristics and water quality in a typical highly intensive agricultural small watershed, Dongting lake basin, south central China.

Science.gov (United States)

Li, Hongqing; Liu, Liming; Ji, Xiang

2015-03-01

Understanding the relationship between landscape characteristics and water quality is critically important for estimating pollution potential and reducing pollution risk. Therefore, this study examines the relationship between landscape characteristics and water quality at both spatial and temporal scales. The study took place in the Jinjing River watershed in 2010; seven landscape types and four water quality pollutions were chosen as analysis parameters. Three different buffer areas along the river were drawn to analyze the relationship as a function of spatial scale. The results of a Pearson's correlation coefficient analysis suggest that "source" landscape, namely, tea gardens, residential areas, and paddy lands, have positive effects on water quality parameters, while forests exhibit a negative influence on water quality parameters because they represent a "sink" landscape and the sub-watershed level is identified as a suitable scale. Using the principal component analysis, tea gardens, residential areas, paddy lands, and forests were identified as the main landscape index. A stepwise multiple regression analysis was employed to model the relationship between landscape characteristics and water quality for each season. The results demonstrate that both landscape composition and configuration affect water quality. In summer and winter, the landscape metrics explained approximately 80.7 % of the variance in the water quality variables, which was higher than that for spring and fall (60.3 %). This study can help environmental managers to understand the relationships between landscapes and water quality and provide landscape ecological approaches for water quality control and land use management.

Prediction of harmful water quality parameters combining weather, air quality and ecosystem models with in situ measurement

Science.gov (United States)

The ability to predict water quality in lakes is important since lakes are sources of water for agriculture, drinking, and recreational uses. Lakes are also home to a dynamic ecosystem of lacustrine wetlands and deep waters. They are sensitive to pH changes and are dependent on d...

Use of Multiple Linear Regression Models for Setting Water Quality Criteria for Copper: A Complementary Approach to the Biotic Ligand Model.

Science.gov (United States)

Brix, Kevin V; DeForest, David K; Tear, Lucinda; Grosell, Martin; Adams, William J

2017-05-02

Biotic Ligand Models (BLMs) for metals are widely applied in ecological risk assessments and in the development of regulatory water quality guidelines in Europe, and in 2007 the United States Environmental Protection Agency (USEPA) recommended BLM-based water quality criteria (WQC) for Cu in freshwater. However, to-date, few states have adopted BLM-based Cu criteria into their water quality standards on a state-wide basis, which appears to be due to the perception that the BLM is too complicated or requires too many input variables. Using the mechanistic BLM framework to first identify key water chemistry parameters that influence Cu bioavailability, namely dissolved organic carbon (DOC), pH, and hardness, we developed Cu criteria using the same basic methodology used by the USEPA to derive hardness-based criteria but with the addition of DOC and pH. As an initial proof of concept, we developed stepwise multiple linear regression (MLR) models for species that have been tested over wide ranges of DOC, pH, and hardness conditions. These models predicted acute Cu toxicity values that were within a factor of ±2 in 77% to 97% of tests (5 species had adequate data) and chronic Cu toxicity values that were within a factor of ±2 in 92% of tests (1 species had adequate data). This level of accuracy is comparable to the BLM. Following USEPA guidelines for WQC development, the species data were then combined to develop a linear model with pooled slopes for each independent parameter (i.e., DOC, pH, and hardness) and species-specific intercepts using Analysis of Covariance. The pooled MLR and BLM models predicted species-specific toxicity with similar precision; adjusted R 2 and R 2 values ranged from 0.56 to 0.86 and 0.66-0.85, respectively. Graphical exploration of relationships between predicted and observed toxicity, residuals and observed toxicity, and residuals and concentrations of key input parameters revealed many similarities and a few key distinctions between the

Community Response to Impaired Drinking Water Quality: Evidence from Bottled Water Sales

Science.gov (United States)

Allaire, M.; Zheng, S.; Lall, U.

2017-12-01

Drinking water contaminants pose a harm to public health. When confronted with elevated contaminate levels, individuals can take averting actions to reduce exposure, such as bottled water purchases. This study addresses a problem of national interest given that 9 to 45 million people have been affected by drinking water quality violations in each of the past 34 years. Moreover, few studies address averting behavior and avoidance costs due to water quality violations. This study assesses how responses might differ across baseline risk of impaired water quality and demographics of service area. We match a panel of weekly supermarket sales data with geocoded violations data for 67 counties in the Southeast from 2006-2015. We estimate the change in bottled water sales due to drinking water violations using a fixed effects model. Observing market behavior also allows us to calculate the cost of these averting actions. Critical findings from this study contribute to understanding how communities respond to water quality violations. We find that violations have considerable effects on bottled water consumption. Sales increase 8.1 percent due to violations related to microorganisms and 31.2 percent due to Tier 1 violations, which pose an immediate health risk. In addition, we calculate a national cost of averting actions of $26 million for microorganism violations from 2006-2015, which represents a lower-bound estimate. Averting costs vary considerably across the U.S. and some counties bear a particularly large burden, such as in California and Texas. Overall, this study provides insight into how averting behavior differs across contaminant type, water utility characteristics, and community demographics. Such knowledge can aid public health agencies, water systems, and environmental regulators to direct assistance to communities most in need.

9 CFR 3.106 - Water quality.

Science.gov (United States)

2010-01-01

... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Water quality. 3.106 Section 3.106... Mammals Animal Health and Husbandry Standards § 3.106 Water quality. (a) General. The primary enclosure... additives (e.g. chlorine and copper) that are added to the water to maintain water quality standards...

Mathematical Modeling for Water Quality Management under Interval and Fuzzy Uncertainties

Directory of Open Access Journals (Sweden)

J. Liu

2013-01-01

Full Text Available In this study, an interval fuzzy credibility-constrained programming (IFCP method is developed for river water quality management. IFCP is derived from incorporating techniques of fuzzy credibility-constrained programming (FCP and interval-parameter programming (IPP within a general optimization framework. IFCP is capable of tackling uncertainties presented as interval numbers and possibility distributions as well as analyzing the reliability of satisfying (or the risk of violating system’s constraints. A real-world case for water quality management planning of the Xiangxi River in the Three Gorges Reservoir Region (which faces severe water quality problems due to pollution from point and nonpoint sources is then conducted for demonstrating the applicability of the developed method. The results demonstrate that high biological oxygen demand (BOD discharge is observed at the Baishahe chemical plant and Gufu wastewater treatment plant. For nonpoint sources, crop farming generates large amounts of total phosphorus (TP and total nitrogen (TN. The results are helpful for managers in not only making decisions of effluent discharges from point and nonpoint sources but also gaining insight into the tradeoff between system benefit and environmental requirement.

Modelling the Impact of Land Use Change on Water Quality in Agricultural Catchments

Science.gov (United States)

Johnes, P. J.; Heathwaite, A. L.

1997-03-01

Export coefficient modelling was used to model the impact of agriculture on nitrogen and phosphorus loading on the surface waters of two contrasting agricultural catchments. The model was originally developed for the Windrush catchment where the highly reactive Jurassic limestone aquifer underlying the catchment is well connected to the surface drainage network, allowing the system to be modelled using uniform export coefficients for each nutrient source in the catchment, regardless of proximity to the surface drainage network. In the Slapton catchment, the hydrological pathways are dominated by surface and lateral shallow subsurface flow, requiring modification of the export coefficient model to incorporate a distance-decay component in the export coefficients. The modified model was calibrated against observed total nitrogen and total phosphorus loads delivered to Slapton Ley from inflowing streams in its catchment. Sensitivity analysis was conducted to isolate the key controls on nutrient export in the modified model. The model was validated against long-term records of water quality, and was found to be accurate in its predictions and sensitive to both temporal and spatial changes in agricultural practice in the catchment. The model was then used to forecast the potential reduction in nutrient loading on Slapton Ley associated with a range of catchment management strategies. The best practicable environmental option (BPEO) was found to be spatial redistribution of high nutrient export risk sources to areas of the catchment with the greatest intrinsic nutrient retention capacity.

[Watershed water environment pollution models and their applications: a review].

Science.gov (United States)

Zhu, Yao; Liang, Zhi-Wei; Li, Wei; Yang, Yi; Yang, Mu-Yi; Mao, Wei; Xu, Han-Li; Wu, Wei-Xiang

2013-10-01

Watershed water environment pollution model is the important tool for studying watershed environmental problems. Through the quantitative description of the complicated pollution processes of whole watershed system and its parts, the model can identify the main sources and migration pathways of pollutants, estimate the pollutant loadings, and evaluate their impacts on water environment, providing a basis for watershed planning and management. This paper reviewed the watershed water environment models widely applied at home and abroad, with the focuses on the models of pollutants loading (GWLF and PLOAD), water quality of received water bodies (QUAL2E and WASP), and the watershed models integrated pollutant loadings and water quality (HSPF, SWAT, AGNPS, AnnAGNPS, and SWMM), and introduced the structures, principles, and main characteristics as well as the limitations in practical applications of these models. The other models of water quality (CE-QUAL-W2, EFDC, and AQUATOX) and watershed models (GLEAMS and MIKE SHE) were also briefly introduced. Through the case analysis on the applications of single model and integrated models, the development trend and application prospect of the watershed water environment pollution models were discussed.

The effects of precipitation, river discharge, land use and coastal circulation on water quality in coastal Maine.

Science.gov (United States)

Tilburg, Charles E; Jordan, Linda M; Carlson, Amy E; Zeeman, Stephan I; Yund, Philip O

2015-07-01

Faecal pollution in stormwater, wastewater and direct run-off can carry zoonotic pathogens to streams, rivers and the ocean, reduce water quality, and affect both recreational and commercial fishing areas of the coastal ocean. Typically, the closure of beaches and commercial fishing areas is governed by the testing for the presence of faecal bacteria, which requires an 18-24 h period for sample incubation. As water quality can change during this testing period, the need for accurate and timely predictions of coastal water quality has become acute. In this study, we: (i) examine the relationship between water quality, precipitation and river discharge at several locations within the Gulf of Maine, and (ii) use multiple linear regression models based on readily obtainable hydrometeorological measurements to predict water quality events at five coastal locations. Analysis of a 12 year dataset revealed that high river discharge and/or precipitation events can lead to reduced water quality; however, the use of only these two parameters to predict water quality can result in a number of errors. Analysis of a higher frequency, 2 year study using multiple linear regression models revealed that precipitation, salinity, river discharge, winds, seasonality and coastal circulation correlate with variations in water quality. Although there has been extensive development of regression models for freshwater, this is one of the first attempts to create a mechanistic model to predict water quality in coastal marine waters. Model performance is similar to that of efforts in other regions, which have incorporated models into water resource managers' decisions, indicating that the use of a mechanistic model in coastal Maine is feasible.

Spectral Band Characterization for Hyperspectral Monitoring of Water Quality

Science.gov (United States)

Vermillion, Stephanie C.; Raqueno, Rolando; Simmons, Rulon

2001-01-01

A method for selecting the set of spectral characteristics that provides the smallest increase in prediction error is of interest to those using hyperspectral imaging (HSI) to monitor water quality. The spectral characteristics of interest to these applications are spectral bandwidth and location. Three water quality constituents of interest that are detectable via remote sensing are chlorophyll (CHL), total suspended solids (TSS), and colored dissolved organic matter (CDOM). Hyperspectral data provides a rich source of information regarding the content and composition of these materials, but often provides more data than an analyst can manage. This study addresses the spectral characteristics need for water quality monitoring for two reasons. First, determination of the greatest contribution of these spectral characteristics would greatly improve computational ease and efficiency. Second, understanding the spectral capabilities of different spectral resolutions and specific regions is an essential part of future system development and characterization. As new systems are developed and tested, water quality managers will be asked to determine sensor specifications that provide the most accurate and efficient water quality measurements. We address these issues using data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and a set of models to predict constituent concentrations.

Fecal coliform management using a coupled hydrodynamics and water quality model for the river Ravi in Pakistan

International Nuclear Information System (INIS)

Haider, H.; Ali, W.

2011-01-01

A Fecal Coliform (FC) management framework is developed incorporating segmentation of river reaches, hydrodynamic and water quality models and FC management under critical winter low flow conditions for a highly polluted River Ravi. FC die-off rate in the river is determined from a field survey of a selected river reach. The travel time calculated with the help of a hydrodynamic model is 0.25 days in the selected reach. FC die-off rate (Kb) was found to be 1.2 day/sup -1/ at 20 degree C. Model calibration with monitoring data set reveals reasonable agreement of the simulation results with the measured field values under low flow conditions. Presently, the river is receiving raw wastewater and the simulation results shows very high fecal coliform levels up to 100 X 10/sup 6/ MPN/100mL in the river water. These levels are much higher than the required recreation and irrigation standards. Simulations are carried out to assess water quality for the future fecal pollution loads in year 2025 and the results reveal that up to 6 log reduction in FC is required at the wastewater out falls, whereas, 5 log reduction would be sufficient for surface drains to meet desired FC standards under low flow conditions. (author)

Comparison Between Water Quality Index (WQI) and Biological Water Quality Index (BWQI) for Water Quality Assessment: Case Study of Melana River, Johor

International Nuclear Information System (INIS)

Nor Zaiha Arman; Mohd Ismid Mohd Said; Shamila Azman; Muhammad Hazim Mat Hussin

2013-01-01

A study of water quality in Melana River, Johor was carried out in three consecutive months (March - May 2012). This study aims to determine the comparative results through biological monitoring as well as conventional method (physical and chemical analysis). Assessment is carried out through collection and identification of the biological indicator which comprises of macro benthos based on Biological Water Quality Index (BWQI). Comparison was done based on two methods namely invertebrate analysis and also laboratory analysis. For invertebrate analysis, Melana River consist of three types of Family groups namely Nymphs, Larvae and Molluscs. The result for Water Quality Index (WQI) and also Biological Water Quality Index (BWQI) analysis showed that the level of Melana River is polluted and classified in Class III. This study shows that even though different methods were used, the similar results were obtained for both rivers and can be applied to any river to identify their level of cleanliness. (author)

The national stream quality accounting network: A flux-basedapproach to monitoring the water quality of large rivers

Science.gov (United States)

Hooper, R.P.; Aulenbach, Brent T.; Kelly, V.J.

2001-01-01

Estimating the annual mass flux at a network of fixed stations is one approach to characterizing water quality of large rivers. The interpretive context provided by annual flux includes identifying source and sink areas for constituents and estimating the loadings to receiving waters, such as reservoirs or the ocean. Since 1995, the US Geological Survey's National Stream Quality Accounting Network (NASQAN) has employed this approach at a network of 39 stations in four of the largest river basins of the USA: The Mississippi, the Columbia, the Colorado and the Rio Grande. In this paper, the design of NASQAN is described and its effectiveness at characterizing the water quality of these rivers is evaluated using data from the first 3 years of operation. A broad range of constituents was measured by NASQAN, including trace organic and inorganic chemicals, major ions, sediment and nutrients. Where possible, a regression model relating concentration to discharge and season was used to interpolate between chemical observations for flux estimation. For water-quality network design, the most important finding from NASQAN was the importance of having a specific objective (that is, estimating annual mass flux) and, from that, an explicitly stated data analysis strategy, namely the use of regression models to interpolate between observations. The use of such models aided in the design of sampling strategy and provided a context for data review. The regression models essentially form null hypotheses for concentration variation that can be evaluated by the observed data. The feedback between network operation and data collection established by the hypothesis tests places the water-quality network on a firm scientific footing.

Water quality indexing for predicting variation of water quality over time

African Journals Online (AJOL)

PPoonoosamy

water, and expressing them to non-technical people may not always be easy. ... parameters for a case study; dissolved oxygen, pH, total coliforms, ... Several national agencies responsible for water supply and water pollution, have strongly .... good quality and required proper treatment if it were to be consumed as potable.

Modeling water demand when households have multiple sources of water

Science.gov (United States)

Coulibaly, Lassina; Jakus, Paul M.; Keith, John E.

2014-07-01

A significant portion of the world's population lives in areas where public water delivery systems are unreliable and/or deliver poor quality water. In response, people have developed important alternatives to publicly supplied water. To date, most water demand research has been based on single-equation models for a single source of water, with very few studies that have examined water demand from two sources of water (where all nonpublic system water sources have been aggregated into a single demand). This modeling approach leads to two outcomes. First, the demand models do not capture the full range of alternatives, so the true economic relationship among the alternatives is obscured. Second, and more seriously, economic theory predicts that demand for a good becomes more price-elastic as the number of close substitutes increases. If researchers artificially limit the number of alternatives studied to something less than the true number, the price elasticity estimate may be biased downward. This paper examines water demand in a region with near universal access to piped water, but where system reliability and quality is such that many alternative sources of water exist. In extending the demand analysis to four sources of water, we are able to (i) demonstrate why households choose the water sources they do, (ii) provide a richer description of the demand relationships among sources, and (iii) calculate own-price elasticity estimates that are more elastic than those generally found in the literature.

Water quality assessment and apportionment of pollution sources using APCS-MLR and PMF receptor modeling techniques in three major rivers of South Florida.

Science.gov (United States)

Haji Gholizadeh, Mohammad; Melesse, Assefa M; Reddi, Lakshmi

2016-10-01

In this study, principal component analysis (PCA), factor analysis (FA), and the absolute principal component score-multiple linear regression (APCS-MLR) receptor modeling technique were used to assess the water quality and identify and quantify the potential pollution sources affecting the water quality of three major rivers of South Florida. For this purpose, 15years (2000-2014) dataset of 12 water quality variables covering 16 monitoring stations, and approximately 35,000 observations was used. The PCA/FA method identified five and four potential pollution sources in wet and dry seasons, respectively, and the effective mechanisms, rules and causes were explained. The APCS-MLR apportioned their contributions to each water quality variable. Results showed that the point source pollution discharges from anthropogenic factors due to the discharge of agriculture waste and domestic and industrial wastewater were the major sources of river water contamination. Also, the studied variables were categorized into three groups of nutrients (total kjeldahl nitrogen, total phosphorus, total phosphate, and ammonia-N), water murkiness conducive parameters (total suspended solids, turbidity, and chlorophyll-a), and salt ions (magnesium, chloride, and sodium), and average contributions of different potential pollution sources to these categories were considered separately. The data matrix was also subjected to PMF receptor model using the EPA PMF-5.0 program and the two-way model described was performed for the PMF analyses. Comparison of the obtained results of PMF and APCS-MLR models showed that there were some significant differences in estimated contribution for each potential pollution source, especially in the wet season. Eventually, it was concluded that the APCS-MLR receptor modeling approach appears to be more physically plausible for the current study. It is believed that the results of apportionment could be very useful to the local authorities for the control and

Using National Coastal Assessment Data to Model Estuarine Water Quality at Large Spatial Scales.

Science.gov (United States)

The water quality of the Nation’s estuaries is attracting scrutiny in light of population growth and enhanced nutrient delivery. The USEPA has evaluated water quality in the National Coastal Assessment (NCA) and National Aquatic Resource Surveys (NARS) programs. Here we rep...

National Recommended Water Quality Criteria

Data.gov (United States)

U.S. Environmental Protection Agency — The National Recommended Water Quality Criteria is a compilation of national recommended water quality criteria for the protection of aquatic life and human health...

British Columbia water quality guidelines (criteria): 1998 edition

Energy Technology Data Exchange (ETDEWEB)

Nagpal, N.K.; Pommen, L.W.; Swain, L.G.

1998-08-01

British Columbia has developed water quality guidelines in order that water quality data can be assessed and site-specific water quality objectives can be prepared. The guidelines provide benchmarks for the assessment of water quality and setting water quality objectives. Guidelines are provided to protect the following six major water uses: drinking water, aquatic life, wildlife, recreation/aesthetics, agriculture, and industrial. Water quality encompasses the physical, chemical and biological quality of the water, sediment and biota. Among other quality criteria the guide provides maximum approved concentrations for nitrogen, aluminum, copper, cyanide, lead, mercury, and molybdenum. 30 tabs.

Socioeconomic dynamics of water quality in the Egyptian Nile

Science.gov (United States)

Malik, Maheen; Nisar, Zainab; Karakatsanis, Georgios

2016-04-01

The Nile River remains the most important source of freshwater for Egypt as it accounts for nearly all of the country's drinking and irrigation water. About 95% of the total population is accounted to live along the Banks of the Nile(1). Therefore, water quality deterioration in addition to general natural scarcity of water in the region(2) is the main driver for carrying out this study. What further aggravates this issue is the water conflict in the Blue Nile region. The study evaluates different water quality parameters and their concentrations in the Egyptian Nile; further assessing the temporal dynamics of water quality in the area with (a) the Environmental Kuznets Curve (EKC)(3) and (b) the Jevons Paradox (JP)(4) in order to identify water quality improvements or degradations using selected socioeconomic variables(5). For this purpose various environmental indicators including BOD, COD, DO, Phosphorus and TDS were plotted against different economic variables including Population, Gross Domestic Product (GDP), Annual Fresh Water Withdrawal and Improved Water Source. Mathematically, this was expressed by 2nd and 3rd degree polynomial regressions generating the EKC and JP respectively. The basic goal of the regression analysis is to model and highlight the dynamic trend of water quality indicators in relation to their established permissible limits, which will allow the identification of optimal future water quality policies. The results clearly indicate that the dependency of water quality indicators on socioeconomic variables differs for every indicator; while COD was above the permissible limits in all the cases despite of its decreasing trend in each case, BOD and phosphate signified increasing concentrations for the future, if they continue to follow the present trend. This could be an indication of rebound effect explained by the Jevons Paradox i.e. water quality deterioration after its improvement, either due to increase of population or intensification

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